Chi, Chia-Fen; Tseng, Li-Kai; Jang, Yuh
2012-07-01
Many disabled individuals lack extensive knowledge about assistive technology, which could help them use computers. In 1997, Denis Anson developed a decision tree of 49 evaluative questions designed to evaluate the functional capabilities of the disabled user and choose an appropriate combination of assistive devices, from a selection of 26, that enable the individual to use a computer. In general, occupational therapists guide the disabled users through this process. They often have to go over repetitive questions in order to find an appropriate device. A disabled user may require an alphanumeric entry device, a pointing device, an output device, a performance enhancement device, or some combination of these. Therefore, the current research eliminates redundant questions and divides Anson's decision tree into multiple independent subtrees to meet the actual demand of computer users with disabilities. The modified decision tree was tested by six disabled users to prove it can determine a complete set of assistive devices with a smaller number of evaluative questions. The means to insert new categories of computer-related assistive devices was included to ensure the decision tree can be expanded and updated. The current decision tree can help the disabled users and assistive technology practitioners to find appropriate computer-related assistive devices that meet with clients' individual needs in an efficient manner.
ERIC Educational Resources Information Center
May, Donald M.; And Others
The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…
Computer-Assisted Diagnostic Decision Support: History, Challenges, and Possible Paths Forward
ERIC Educational Resources Information Center
Miller, Randolph A.
2009-01-01
This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References…
Deep learning aided decision support for pulmonary nodules diagnosing: a review.
Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo
2018-04-01
Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.
Computer-assisted diagnostic decision support: history, challenges, and possible paths forward.
Miller, Randolph A
2009-09-01
This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References indicate the original sources of many of these ideas.
Implementing Computer Technology in the Rehabilitation Process.
ERIC Educational Resources Information Center
McCollum, Paul S., Ed.; Chan, Fong, Ed.
1985-01-01
This special issue contains seven articles, addressing rehabilitation in the information age, computer-assisted rehabilitation services, computer technology in rehabilitation counseling, computer-assisted career exploration and vocational decision making, computer-assisted assessment, computer enhanced employment opportunities for persons with…
Federal Register 2010, 2011, 2012, 2013, 2014
2012-07-03
...] Guidances for Industry and Food and Drug Administration Staff: Computer-Assisted Detection Devices Applied... Clinical Performance Assessment: Considerations for Computer-Assisted Detection Devices Applied to... guidance, entitled ``Computer-Assisted Detection Devices Applied to Radiology Images and Radiology Device...
Deep learning aided decision support for pulmonary nodules diagnosing: a review
Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping
2018-01-01
Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing. PMID:29780633
Zühlke, Liesl J; Engel, Mark E; Nkepu, Simpiwe; Mayosi, Bongani M
2016-08-01
Introduction Echocardiography is the diagnostic test of choice for latent rheumatic heart disease. The utility of echocardiography for large-scale screening is limited by high cost, complex diagnostic protocols, and time to acquire multiple images. We evaluated the performance of a brief hand-held echocardiography protocol and computer-assisted auscultation in detecting latent rheumatic heart disease with or without pathological murmur. A total of 27 asymptomatic patients with latent rheumatic heart disease based on the World Heart Federation criteria and 66 healthy controls were examined by standard cardiac auscultation to detect pathological murmur. Hand-held echocardiography using a focussed protocol that utilises one view - that is, the parasternal long-axis view - and one measurement - that is, mitral regurgitant jet - and a computer-assisted auscultation utilising an automated decision tool were performed on all patients. The sensitivity and specificity of computer-assisted auscultation in latent rheumatic heart disease were 4% (95% CI 1.0-20.4%) and 93.7% (95% CI 84.5-98.3%), respectively. The sensitivity and specificity of the focussed hand-held echocardiography protocol for definite rheumatic heart disease were 92.3% (95% CI 63.9-99.8%) and 100%, respectively. The test reliability of hand-held echocardiography was 98.7% for definite and 94.7% for borderline disease, and the adjusted diagnostic odds ratios were 1041 and 263.9 for definite and borderline disease, respectively. Computer-assisted auscultation has extremely low sensitivity but high specificity for pathological murmur in latent rheumatic heart disease. Focussed hand-held echocardiography has fair sensitivity but high specificity and diagnostic utility for definite or borderline rheumatic heart disease in asymptomatic patients.
Computer-assisted image analysis to quantify daily growth rates of broiler chickens.
De Wet, L; Vranken, E; Chedad, A; Aerts, J M; Ceunen, J; Berckmans, D
2003-09-01
1. The objective was to investigate the possibility of detecting daily body weight changes of broiler chickens with computer-assisted image analysis. 2. The experiment included 50 broiler chickens reared under commercial conditions. Ten out of 50 chickens were randomly selected and video recorded (upper view) 18 times during the 42-d growing period. The number of surface and periphery pixels from the images was used to derive a relationship between body dimension and live weight. 3. The relative error in weight estimation, expressed in terms of the standard deviation of the residuals from image surface data was 10%, while it was found to be 15% for the image periphery data. 4. Image-processing systems could be developed to assist the farmer in making important management and marketing decisions.
[Computed tomography with computer-assisted detection of pulmonary nodules in dogs and cats].
Niesterok, C; Piesnack, S; Köhler, C; Ludewig, E; Alef, M; Kiefer, I
2015-01-01
The aim of this study was to assess the potential benefit of computer-assisted detection (CAD) of pulmonary nodules in veterinary medicine. Therefore, the CAD rate was compared to the detection rates of two individual examiners in terms of its sensitivity and false-positive findings. We included 51 dogs and 16 cats with pulmonary nodules previously diagnosed by computed tomography. First, the number of nodules ≥ 3 mm was recorded for each patient by two independent examiners. Subsequently, each examiner used the CAD software for automated nodule detection. With the knowledge of the CAD results, a final consensus decision on the number of nodules was achieved. The software used was a commercially available CAD program. The sensitivity of examiner 1 was 89.2%, while that of examiner 2 reached 87.4%. CAD had a sensitivity of 69.4%. With CAD, the sensitivity of examiner 1 increased to 94.7% and that of examiner 2 to 90.8%. The CAD-system, which we used in our study, had a moderate sensitivity of 69.4%. Despite its severe limitations, with a high level of false-positive and false-negative results, CAD increased the examiners' sensitivity. Therefore, its supportive role in diagnostics appears to be evident.
Jaya, T; Dheeba, J; Singh, N Albert
2015-12-01
Diabetic retinopathy is a major cause of vision loss in diabetic patients. Currently, there is a need for making decisions using intelligent computer algorithms when screening a large volume of data. This paper presents an expert decision-making system designed using a fuzzy support vector machine (FSVM) classifier to detect hard exudates in fundus images. The optic discs in the colour fundus images are segmented to avoid false alarms using morphological operations and based on circular Hough transform. To discriminate between the exudates and the non-exudates pixels, colour and texture features are extracted from the images. These features are given as input to the FSVM classifier. The classifier analysed 200 retinal images collected from diabetic retinopathy screening programmes. The tests made on the retinal images show that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and features sets, the area under the receiver operating characteristic curve reached 0.9606, which corresponds to a sensitivity of 94.1% with a specificity of 90.0%. The results suggest that detecting hard exudates using FSVM contribute to computer-assisted detection of diabetic retinopathy and as a decision support system for ophthalmologists.
The Contribution of a Decision Support System to Educational Decision-Making Processes
ERIC Educational Resources Information Center
Klein, Joseph; Ronen, Herman
2003-01-01
In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…
Automatic colonic lesion detection and tracking in endoscopic videos
NASA Astrophysics Data System (ADS)
Li, Wenjing; Gustafsson, Ulf; A-Rahim, Yoursif
2011-03-01
The biology of colorectal cancer offers an opportunity for both early detection and prevention. Compared with other imaging modalities, optical colonoscopy is the procedure of choice for simultaneous detection and removal of colonic polyps. Computer assisted screening makes it possible to assist physicians and potentially improve the accuracy of the diagnostic decision during the exam. This paper presents an unsupervised method to detect and track colonic lesions in endoscopic videos. The aim of the lesion screening and tracking is to facilitate detection of polyps and abnormal mucosa in real time as the physician is performing the procedure. For colonic lesion detection, the conventional marker controlled watershed based segmentation is used to segment the colonic lesions, followed by an adaptive ellipse fitting strategy to further validate the shape. For colonic lesion tracking, a mean shift tracker with background modeling is used to track the target region from the detection phase. The approach has been tested on colonoscopy videos acquired during regular colonoscopic procedures and demonstrated promising results.
A Knowledge-Based System for the Computer Assisted Diagnosis of Endoscopic Images
NASA Astrophysics Data System (ADS)
Kage, Andreas; Münzenmayer, Christian; Wittenberg, Thomas
Due to the actual demographic development the use of Computer-Assisted Diagnosis (CAD) systems becomes a more important part of clinical workflows and clinical decision making. Because changes on the mucosa of the esophagus can indicate the first stage of cancerous developments, there is a large interest to detect and correctly diagnose any such lesion. We present a knowledge-based system which is able to support a physician with the interpretation and diagnosis of endoscopic images of the esophagus. Our system is designed to support the physician directly during the examination of the patient, thus prodving diagnostic assistence at the point of care (POC). Based on an interactively marked region in an endoscopic image of interest, the system provides a diagnostic suggestion, based on an annotated reference image database. Furthermore, using relevant feedback mechanisms, the results can be enhanced interactively.
Computer-assisted abdominal surgery: new technologies.
Kenngott, H G; Wagner, M; Nickel, F; Wekerle, A L; Preukschas, A; Apitz, M; Schulte, T; Rempel, R; Mietkowski, P; Wagner, F; Termer, A; Müller-Stich, Beat P
2015-04-01
Computer-assisted surgery is a wide field of technologies with the potential to enable the surgeon to improve efficiency and efficacy of diagnosis, treatment, and clinical management. This review provides an overview of the most important new technologies and their applications. A MEDLINE database search was performed revealing a total of 1702 references. All references were considered for information on six main topics, namely image guidance and navigation, robot-assisted surgery, human-machine interface, surgical processes and clinical pathways, computer-assisted surgical training, and clinical decision support. Further references were obtained through cross-referencing the bibliography cited in each work. Based on their respective field of expertise, the authors chose 64 publications relevant for the purpose of this review. Computer-assisted systems are increasingly used not only in experimental studies but also in clinical studies. Although computer-assisted abdominal surgery is still in its infancy, the number of studies is constantly increasing, and clinical studies start showing the benefits of computers used not only as tools of documentation and accounting but also for directly assisting surgeons during diagnosis and treatment of patients. Further developments in the field of clinical decision support even have the potential of causing a paradigm shift in how patients are diagnosed and treated.
ERIC Educational Resources Information Center
Ballantine, R. Malcolm
Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…
Role of Computer Assisted Instruction (CAI) in an Introductory Computer Concepts Course.
ERIC Educational Resources Information Center
Skudrna, Vincent J.
1997-01-01
Discusses the role of computer assisted instruction (CAI) in undergraduate education via a survey of related literature and specific applications. Describes an undergraduate computer concepts course and includes appendices of instructions, flowcharts, programs, sample student work in accounting, COBOL instructional model, decision logic in a…
Computer-Aided Diagnosis in Medical Imaging: Historical Review, Current Status and Future Potential
Doi, Kunio
2007-01-01
Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. In this article, the motivation and philosophy for early development of CAD schemes are presented together with the current status and future potential of CAD in a PACS environment. With CAD, radiologists use the computer output as a “second opinion” and make the final decisions. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral chest images has the potential to improve the overall performance in the detection of lung nodules when combined with another CAD scheme for PA chest images. Because vertebral fractures can be detected reliably by computer on lateral chest radiographs, radiologists’ accuracy in the detection of vertebral fractures would be improved by the use of CAD, and thus early diagnosis of osteoporosis would become possible. In MRA, a CAD system has been developed for assisting radiologists in the detection of intracranial aneurysms. On successive bone scan images, a CAD scheme for detection of interval changes has been developed by use of temporal subtraction images. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for chest CAD may include the computerized detection of lung nodules, interstitial opacities, cardiomegaly, vertebral fractures, and interval changes in chest radiographs as well as the computerized classification of benign and malignant nodules and the differential diagnosis of interstitial lung diseases. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with known pathology, which would be very similar to a new unknown case, from PACS when a reliable and useful method has been developed for quantifying the similarity of a pair of images for visual comparison by radiologists. PMID:17349778
Training of perceptual-cognitive skills in offside decision making.
Catteeuw, Peter; Gilis, Bart; Jaspers, Arne; Wagemans, Johan; Helsen, Werner
2010-12-01
This study investigates the effect of two off-field training formats to improve offside decision making. One group trained with video simulations and another with computer animations. Feedback after every offside situation allowed assistant referees to compensate for the consequences of the flash-lag effect and to improve their decision-making accuracy. First, response accuracy improved and flag errors decreased for both training groups implying that training interventions with feedback taught assistant referees to better deal with the flash-lag effect. Second, the results demonstrated no effect of format, although assistant referees rated video simulations higher for fidelity than computer animations. This implies that a cognitive correction to a perceptual effect can be learned also when the format does not correspond closely with the original perceptual situation. Off-field offside decision-making training should be considered as part of training because it is a considerable help to gain more experience and to improve overall decision-making performance.
Expert Systems: Tutors, Tools, and Tutees.
ERIC Educational Resources Information Center
Lippert, Renate C.
1989-01-01
Discusses the current status, research, and practical implications of artificial intelligence and expert systems in education. Topics discussed include computer-assisted instruction; intelligent computer-assisted instruction; intelligent tutoring systems; instructional strategies involving the creation of knowledge bases; decision aids;…
Computer-assisted instruction in curricula of physical therapist assistants.
Thompson, E C
1987-08-01
This article compares the effectiveness of computer-assisted instruction (CAI) with written, programmed instruction between two groups of physical therapist assistant students. No significant difference in the amount of material learned or retained after completion of testing using either CAI or a written, programmed text was found in this group of 16 subjects. Learning style or attitude about computers did not correlate strongly with performance after the CAI. Findings suggest that more research is needed to support decisions related to fiscal allotments for computer use in college curricula.
Gross, Seth A; Smith, Michael S; Kaul, Vivek
2017-01-01
Background Barrett’s esophagus (BE) and esophageal dysplasia (ED) are frequently missed during screening and surveillance esophagoscopy because of sampling error associated with four-quadrant random forceps biopsy (FB). Aim The aim of this article is to determine if wide-area transepithelial sampling with three-dimensional computer-assisted analysis (WATS) used adjunctively with FB can increase the detection of BE and ED. Methods In this multicenter prospective trial, patients screened for suspected BE and those with known BE undergoing surveillance were enrolled. Patients at 25 community-based practices underwent WATS adjunctively to targeted FB and random four-quadrant FB. Results Of 4203 patients, 594 were diagnosed with BE by FB alone, and 493 additional cases were detected by adding WATS, increasing the overall detection of BE by 83% (493/594, 95% CI 74%–93%). Low-grade dysplasia (LGD) was diagnosed in 26 patients by FB alone, and 23 additional cases were detected by adding WATS, increasing the detection of LGD by 88.5% (23/26, 95% CI 48%–160%). Conclusions Adjunctive use of WATS to FB significantly improves the detection of both BE and ED. Sampling error, an inherent limitation associated with screening and surveillance, can be improved with WATS allowing better informed decisions to be made about the management and subsequent treatment of these patients. PMID:29881608
Computer Assisted Thermography And Its Application In Ovulation Detection
NASA Astrophysics Data System (ADS)
Rao, K. H.; Shah, A. V.
1984-08-01
Hardware and software of a computer-assisted image analyzing system used for infrared images in medical applications are discussed. The application of computer-assisted thermography (CAT) as a complementary diagnostic tool in centralized diagnostic management is proposed. The authors adopted 'Computer Assisted Thermography' to study physiological changes in the breasts related to the hormones characterizing the menstrual cycle of a woman. Based on clinical experi-ments followed by thermal image analysis, they suggest that 'differential skin temperature (DST)1 be measured to detect the fertility interval in the menstrual cycle of a woman.
Computer-assisted navigation in orthopedic surgery.
Mavrogenis, Andreas F; Savvidou, Olga D; Mimidis, George; Papanastasiou, John; Koulalis, Dimitrios; Demertzis, Nikolaos; Papagelopoulos, Panayiotis J
2013-08-01
Computer-assisted navigation has a role in some orthopedic procedures. It allows the surgeons to obtain real-time feedback and offers the potential to decrease intra-operative errors and optimize the surgical result. Computer-assisted navigation systems can be active or passive. Active navigation systems can either perform surgical tasks or prohibit the surgeon from moving past a predefined zone. Passive navigation systems provide intraoperative information, which is displayed on a monitor, but the surgeon is free to make any decisions he or she deems necessary. This article reviews the available types of computer-assisted navigation, summarizes the clinical applications and reviews the results of related series using navigation, and informs surgeons of the disadvantages and pitfalls of computer-assisted navigation in orthopedic surgery. Copyright 2013, SLACK Incorporated.
ERIC Educational Resources Information Center
Vos, Hans J.
As part of a project formulating optimal rules for decision making in computer assisted instructional systems in which the computer is used as a decision support tool, an approach that simultaneously optimizes classification of students into two treatments, each followed by a mastery decision, is presented using the framework of Bayesian decision…
Development of an assisting detection system for early infarct diagnosis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sim, K. S.; Nia, M. E.; Ee, C. S.
2015-04-24
In this paper, a detection assisting system for early infarct detection is developed. This new developed method is used to assist the medical practitioners to diagnose infarct from computed tomography images of brain. Using this assisting system, the infarct could be diagnosed at earlier stages. The non-contrast computed tomography (NCCT) brain images are the data set used for this system. Detection module extracts the pixel data from NCCT brain images, and produces the colourized version of images. The proposed method showed great potential in detecting infarct, and helps medical practitioners to make earlier and better diagnoses.
Computer-Assisted Instruction to Avert Teen Pregnancy.
ERIC Educational Resources Information Center
Starn, Jane Ryburn; Paperny, David M.
Teenage pregnancy has become a major public health problem in the United States. A study was conducted to assess an intervention based upon computer-assisted instruction (CAI) to avert teenage pregnancy. Social learning and decision theory were applied to mediate the adolescent environment through CAI so that adolescent development would be…
ERIC Educational Resources Information Center
Lynch, William W.
Prompting of reading errors is a common pattern of teaching behavior occurring in reading groups. Teachers' tactics in responding to pupil errors during oral reading in public school classrooms were analyzed with the assistance of the technology of the Computer Assisted Teacher Training System (CATTS) to formulate hypotheses about teacher decision…
Computer-Assisted Community Planning and Decision Making.
ERIC Educational Resources Information Center
College of the Atlantic, Bar Harbor, ME.
The College of the Atlantic (COA) developed a broad-based, interdisciplinary curriculum in ecological policy and community planning and decision-making that incorporates two primary computer-based tools: ARC/INFO Geographic Information System (GIS) and STELLA, a systems-dynamics modeling tool. Students learn how to use and apply these tools…
ERIC Educational Resources Information Center
Brown, Johanna Michele
2011-01-01
Career decision making difficulty, as it relates to undecided college students and career indecision, has been a concern for counselors and academic advisors for decades (Gordon, 2006; Mau, 2004). Individuals struggling with career indecision often seek assistance via career counseling, self-help tools, and/or computer-assisted career guidance…
Computer modeling of human decision making
NASA Technical Reports Server (NTRS)
Gevarter, William B.
1991-01-01
Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making.
ERIC Educational Resources Information Center
Hattie, John A. C.; Brown, Gavin T. L.
2008-01-01
National assessment systems can be enhanced with effective school-based assessment (SBA) that allows teachers to focus on improvement decisions. Modern computer-assisted technology systems are often used to deploy SBA systems. Since 2000, New Zealand has researched, developed, and deployed a national, computer-assisted SBA system. Eight major…
Group Augmentation in Realistic Visual-Search Decisions via a Hybrid Brain-Computer Interface.
Valeriani, Davide; Cinel, Caterina; Poli, Riccardo
2017-08-10
Groups have increased sensing and cognition capabilities that typically allow them to make better decisions. However, factors such as communication biases and time constraints can lead to less-than-optimal group decisions. In this study, we use a hybrid Brain-Computer Interface (hBCI) to improve the performance of groups undertaking a realistic visual-search task. Our hBCI extracts neural information from EEG signals and combines it with response times to build an estimate of the decision confidence. This is used to weigh individual responses, resulting in improved group decisions. We compare the performance of hBCI-assisted groups with the performance of non-BCI groups using standard majority voting, and non-BCI groups using weighted voting based on reported decision confidence. We also investigate the impact on group performance of a computer-mediated form of communication between members. Results across three experiments suggest that the hBCI provides significant advantages over non-BCI decision methods in all cases. We also found that our form of communication increases individual error rates by almost 50% compared to non-communicating observers, which also results in worse group performance. Communication also makes reported confidence uncorrelated with the decision correctness, thereby nullifying its value in weighing votes. In summary, best decisions are achieved by hBCI-assisted, non-communicating groups.
CAD system for automatic analysis of CT perfusion maps
NASA Astrophysics Data System (ADS)
Hachaj, T.; Ogiela, M. R.
2011-03-01
In this article, authors present novel algorithms developed for the computer-assisted diagnosis (CAD) system for analysis of dynamic brain perfusion, computer tomography (CT) maps, cerebral blood flow (CBF), and cerebral blood volume (CBV). Those methods perform both quantitative analysis [detection and measurement and description with brain anatomy atlas (AA) of potential asymmetries/lesions] and qualitative analysis (semantic interpretation of visualized symptoms). The semantic interpretation (decision about type of lesion: ischemic/hemorrhagic, is the brain tissue at risk of infraction or not) of visualized symptoms is done by, so-called, cognitive inference processes allowing for reasoning on character of pathological regions based on specialist image knowledge. The whole system is implemented in.NET platform (C# programming language) and can be used on any standard PC computer with.NET framework installed.
Neubert, Antje; Dormann, Harald; Prokosch, Hans-Ulrich; Bürkle, Thomas; Rascher, Wolfgang; Sojer, Reinhold; Brune, Kay; Criegee-Rieck, Manfred
2013-09-01
Computer-assisted signal generation is an important issue for the prevention of adverse drug reactions (ADRs). However, due to poor standardization of patients' medical data and a lack of computable medical drug knowledge the specificity of computerized decision support systems for early ADR detection is too low and thus those systems are not yet implemented in daily clinical practice. We report on a method to formalize knowledge about ADRs based on the Summary of Product Characteristics (SmPCs) and linking them with structured patient data to generate safety signals automatically and with high sensitivity and specificity. A computable ADR knowledge base (ADR-KB) that inherently contains standardized concepts for ADRs (WHO-ART), drugs (ATC) and laboratory test results (LOINC) was built. The system was evaluated in study populations of paediatric and internal medicine inpatients. A total of 262 different ADR concepts related to laboratory findings were linked to 212 LOINC terms. The ADR knowledge base was retrospectively applied to a study population of 970 admissions (474 internal and 496 paediatric patients), who underwent intensive ADR surveillance. The specificity increased from 7% without ADR-KB up to 73% in internal patients and from 19.6% up to 91% in paediatric inpatients, respectively. This study shows that contextual linkage of patients' medication data with laboratory test results is a useful and reasonable instrument for computer-assisted ADR detection and a valuable step towards a systematic drug safety process. The system enables automated detection of ADRs during clinical practice with a quality close to intensive chart review. © 2013 The Authors. British Journal of Clinical Pharmacology © 2013 The British Pharmacological Society.
ERIC Educational Resources Information Center
Bessent, E. Wailand; And Others
Provided in the manual are background material, problems, and worksheets designed for graduate students involved in a computer assisted instruction (CAI) approach to supervisor training. Included are a faculty handbook for a simulated school in a mythical community, a practice problem to familiarize the student with terminal operation, and eight…
A Framework for the Design of Computer-Assisted Simulation Training for Complex Police Situations
ERIC Educational Resources Information Center
Söderström, Tor; Åström, Jan; Anderson, Greg; Bowles, Ron
2014-01-01
Purpose: The purpose of this paper is to report progress concerning the design of a computer-assisted simulation training (CAST) platform for developing decision-making skills in police students. The overarching aim is to outline a theoretical framework for the design of CAST to facilitate police students' development of search techniques in…
Computer-Assisted Career Guidance Systems: A Part of NCDA History
ERIC Educational Resources Information Center
Harris-Bowlsbey, JoAnn
2013-01-01
The first computer-assisted career planning systems were developed in the late 1960s and were based soundly on the best of career development and decision-making theory. Over the years, this tradition has continued as the technology that delivers these systems' content has improved dramatically and as they have been universally accepted as…
Real time simulation of computer-assisted sequencing of terminal area operations
NASA Technical Reports Server (NTRS)
Dear, R. G.
1981-01-01
A simulation was developed to investigate the utilization of computer assisted decision making for the task of sequencing and scheduling aircraft in a high density terminal area. The simulation incorporates a decision methodology termed Constrained Position Shifting. This methodology accounts for aircraft velocity profiles, routes, and weight classes in dynamically sequencing and scheduling arriving aircraft. A sample demonstration of Constrained Position Shifting is presented where six aircraft types (including both light and heavy aircraft) are sequenced to land at Denver's Stapleton International Airport. A graphical display is utilized and Constrained Position Shifting with a maximum shift of four positions (rearward or forward) is compared to first come, first serve with respect to arrival at the runway. The implementation of computer assisted sequencing and scheduling methodologies is investigated. A time based control concept will be required and design considerations for such a system are discussed.
ERIC Educational Resources Information Center
Hopf-Weichel, Rosemarie; And Others
This report describes results of the first year of a three-year program to develop and evaluate a new Adaptive Computerized Training System (ACTS) for electronics maintenance training. (ACTS incorporates an adaptive computer program that learns the student's diagnostic and decision value structure, compares it to that of an expert, and adapts the…
Towards a Framework for Making Effective Computational Choices: A "Very Big Idea" of Mathematics
ERIC Educational Resources Information Center
Hurst, Chris
2016-01-01
It is important for students to make informed decisions about computation. This article highlights this importance and develops a framework which may assist teachers to help students to make effective computational choices.
NASA Astrophysics Data System (ADS)
Rajabzadeh-Oghaz, Hamidreza; Varble, Nicole; Davies, Jason M.; Mowla, Ashkan; Shakir, Hakeem J.; Sonig, Ashish; Shallwani, Hussain; Snyder, Kenneth V.; Levy, Elad I.; Siddiqui, Adnan H.; Meng, Hui
2017-03-01
Neurosurgeons currently base most of their treatment decisions for intracranial aneurysms (IAs) on morphological measurements made manually from 2D angiographic images. These measurements tend to be inaccurate because 2D measurements cannot capture the complex geometry of IAs and because manual measurements are variable depending on the clinician's experience and opinion. Incorrect morphological measurements may lead to inappropriate treatment strategies. In order to improve the accuracy and consistency of morphological analysis of IAs, we have developed an image-based computational tool, AView. In this study, we quantified the accuracy of computer-assisted adjuncts of AView for aneurysmal morphologic assessment by performing measurement on spheres of known size and anatomical IA models. AView has an average morphological error of 0.56% in size and 2.1% in volume measurement. We also investigate the clinical utility of this tool on a retrospective clinical dataset and compare size and neck diameter measurement between 2D manual and 3D computer-assisted measurement. The average error was 22% and 30% in the manual measurement of size and aneurysm neck diameter, respectively. Inaccuracies due to manual measurements could therefore lead to wrong treatment decisions in 44% and inappropriate treatment strategies in 33% of the IAs. Furthermore, computer-assisted analysis of IAs improves the consistency in measurement among clinicians by 62% in size and 82% in neck diameter measurement. We conclude that AView dramatically improves accuracy for morphological analysis. These results illustrate the necessity of a computer-assisted approach for the morphological analysis of IAs.
2017-10-01
hypothesis that a computer machine learning algorithm can analyze and classify burn injures using multispectral imaging within 5% of an expert clinician...morbidity. In response to these challenges, the USAISR developed and obtained FDA 510(k) clearance of the Burn Navigator™, a computer decision support... computer decision support software (CDSS), can significantly change the CDSS algorithm’s recommendations and thus the total fluid administered to a
Shared Decisions & Technology-Assisted Learning
ERIC Educational Resources Information Center
Jacobs, Mary
2005-01-01
In this short article, the author discusses how Henderson Middle School in Jackson, Georgia used shared decision making to improve student achievement through the use of laptop computers. With effective use of technology and shared decision making, administrators at Henderson believe that they can continue to achieve Adequate Yearly Progress under…
ERIC Educational Resources Information Center
Ferguson, Richard L.
The focus of this study was upon the development and evaluation of a computer-assisted branched test to be used in making instructional decisions for individuals in the program of Individually Prescribed Instruction. A Branched Test is one in which the presentation of test items is contingent upon the previous responses of the examinee. The…
Decision making and problem solving with computer assistance
NASA Technical Reports Server (NTRS)
Kraiss, F.
1980-01-01
In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles.
Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey
Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan
2013-01-01
The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259
Duroy, David; Boutron, Isabelle; Baron, Gabriel; Ravaud, Philippe; Estellat, Candice; Lejoyeux, Michel
2016-08-01
To assess the impact of a computer-assisted Screening, Brief Intervention, and Referral to Treatment (SBIRT) on daily consumption of alcohol by patients with hazardous drinking disorder detected after systematic screening during their admission to an emergency department (ED). Two-arm, parallel group, multicentre, randomized controlled trial with a centralised computer-generated randomization procedure. Four EDs in university hospitals located in the Paris area in France. Patients admitted in the ED for any reason, with hazardous drinking disorder detected after systematic screening (i.e., Alcohol Use Disorder Identification Test score ≥5 for women and 8 for men OR self-reported alcohol consumption by week ≥7 drinks for women and 14 for men). The experimental intervention was computer-assisted SBIRT and the comparator was a placebo-controlled intervention (i.e., a computer-assisted education program on nutrition). Interventions were administered in the ED and followed by phone reinforcements at 1 and 3 months. The primary outcome was the mean number of alcohol drinks per day in the previous week, at 12 months. Results From May 2005 to February 2011, 286 patients were randomized to the computer-assisted SBIRT and 286 to the comparator intervention. The two groups did not differ in the primary outcome, with an adjusted mean difference of 0.12 (95% confidence interval, -0.88 to 1.11). There was no additional benefit of the computer-assisted alcohol SBIRT as compared with the computer-assisted education program on nutrition among patients with hazardous drinking disorder detected by systematic screening during their admission to an ED. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Estimating the Reliability of the CITAR Computer Courseware Evaluation System.
ERIC Educational Resources Information Center
Micceri, Theodore
In today's complex computer-based teaching (CBT)/computer-assisted instruction market, flashy presentations frequently prove the most important purchasing element, while instructional design and content are secondary to form. Courseware purchasers must base decisions upon either a vendor's presentation or some published evaluator rating.…
Computer-Assisted Pregnancy Management
Haug, Peter J.; Hebertson, Richard M.; Heywood, Reed E.; Larkin, Ronald; Swapp, Craig; Waterfall, Brian; Warner, Homer R.
1987-01-01
A computer system under development for the management of pregnancy is described. This system exploits expert systems tools in the HELP Hospital Information System to direct the collection of clinical data and to generate medical decisions aimed at enhancing and standardizing prenatal care.
2005-09-01
ENGINEERING APPROACH TO INTELLIGENT OPERATOR ASSISTANCE AND AUTONOMOUS VEHICLE GUIDANCE ..................100 27. SHARPLE, SARAH (WITH COX, GEMMA & STEDMON...104 30. TANGO, FABIO: CONCEPT OF AUTONOMIC COMPUTING APPLIED TO TRANSPORTATION ISSUES: THE SENSITIVE CAR .....105 31. TAYLOR, ROBERT: POSITION...SYSTEMS ENGINEERING APPROACH TO INTELLIGENT OPERATOR ASSISTANCE AND AUTONOMOUS VEHICLE GUIDANCE Today’s automation systems are typically introduced
Decision Analysis Using Spreadsheets.
ERIC Educational Resources Information Center
Sounderpandian, Jayavel
1989-01-01
Discussion of decision analysis and its importance in a business curriculum focuses on the use of spreadsheets instead of commercial software packages for computer assisted instruction. A hypothetical example is given of a company drilling for oil, and suggestions are provided for classroom exercises using spreadsheets. (seven references) (LRW)
Bayesian design of decision rules for failure detection
NASA Technical Reports Server (NTRS)
Chow, E. Y.; Willsky, A. S.
1984-01-01
The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one.
Ischemic stroke enhancement in computed tomography scans using a computational approach
NASA Astrophysics Data System (ADS)
Alves, Allan F. F.; Pavan, Ana L. M.; Jennane, Rachid; Miranda, José R. A.; Freitas, Carlos C. M.; Abdala, Nitamar; Pina, Diana R.
2018-03-01
In this work, a novel approach was proposed to enhance the visual perception of ischemic stroke in computed tomography scans. Through different image processing techniques, we enabled less experienced physicians, to reliably detect early signs of stroke. A set of 40 retrospective CT scans of patients were used, divided into two groups: 25 cases of acute ischemic stroke and 15 normal cases used as control group. All cases were obtained within 4 hours of symptoms onset. Our approach was based on the variational decomposition model and three different segmentation methods. A test determined observers' performance to correctly diagnose stroke cases. The Expectation Maximization method provided the best results among all observers. The overall sensitivity of the observer's analysis was 64% and increased to 79%. The overall specificity was 67% and increased to 78%. These results show the importance of a computational tool to assist neuroradiology decisions, especially in critical situations such as the diagnosis of ischemic stroke.
Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan
2008-03-01
This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Fédération Internationale de Football Association (FIFA; n = 29) and Belgian elite (n = 28) assistant referees (ARs) assessed 64 computer-based offside situations. First, an expertise effect was found. The FIFA ARs assessed the trials more accurately than the Belgian ARs (76.4% vs. 67.5%). Second, regarding the type of error, all ARs clearly tended to raise their flag in doubtful situations. This observation could be explained by a perceptual bias associated with the flash-lag effect. Specifically, attackers were perceived ahead of their actual positions, and this tendency was stronger for the Belgian than for the FIFA ARs (11.0 vs. 8.4 pixels), in particular when the difficulty of the trials increased. Further experimentation is needed to examine whether video- and computer-based decision-making training is effective in improving the decision-making skills of ARs during the game. PsycINFO Database Record (c) 2008 APA, all rights reserved
Apply creative thinking of decision support in electrical nursing record.
Hao, Angelica Te-Hui; Hsu, Chien-Yeh; Li-Fang, Huang; Jian, Wen-Shan; Wu, Li-Bin; Kao, Ching-Chiu; Lu, Mei-Show; Chang, Her-Kung
2006-01-01
The nursing process consists of five interrelated steps: assessment, diagnosis, planning, intervention, and evaluation. In the nursing process, the nurse collects a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Computer systems are viewed as tools to expand the capabilities of the nurse's mind. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most fundamental decision support--i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to generate nursing diagnoses from data and how to individualize the care plans still reminds of the nurse. The purpose of this study is to develop a pilot structure in electronic nursing record system integrated with international nursing standard for improving the proficiency and accuracy of plan of care in clinical pathway process. The proposed pilot systems not only assist both student nurses and nurses who are novice in nursing practice, but also experts who need to work in a practice area which they are not familiar with.
Graphics; For Regional Policy Making, a Preliminary Study.
ERIC Educational Resources Information Center
Ewald, William R., Jr.
The use of graphics (maps, charts, diagrams, renderings, photographs) for regional policy formulation and decision making is discussed at length. The report identifies the capabilities of a number of tools for analysis/synthesis/communication, especially computer assisted graphics to assist in community self-education and the management of change.…
The Use of Microcomputers in the Treatment of Cognitive-Communicative Impairments.
ERIC Educational Resources Information Center
Story, Tamara B.; Sbordone, Robert J.
1988-01-01
The use of microcomputer-assisted therapy as part of the total rehabilitation plan for brain-injured individuals with cognitive-communicative impairments is addressed. Design of effective computer-assisted remediation requires a careful decision-making process. Specific types of software are suggested for dealing with deficits in organization,…
Medical imaging and registration in computer assisted surgery.
Simon, D A; Lavallée, S
1998-09-01
Imaging, sensing, and computing technologies that are being introduced to aid in the planning and execution of surgical procedures are providing orthopaedic surgeons with a powerful new set of tools for improving clinical accuracy, reliability, and patient outcomes while reducing costs and operating times. Current computer assisted surgery systems typically include a measurement process for collecting patient specific medical data, a decision making process for generating a surgical plan, a registration process for aligning the surgical plan to the patient, and an action process for accurately achieving the goals specified in the plan. Some of the key concepts in computer assisted surgery applied to orthopaedics with a focus on the basic framework and underlying technologies is outlined. In addition, technical challenges and future trends in the field are discussed.
1988-03-14
focused application of decision aids. These decision aids must incorporate standardized processes, computer assisted artificial intelligence, linkage...Theater Planning. A Strategic-Operational Perspective,’ by COL MIke ,or i n Olesak, John, LTC Office of the Deputy Chief of Staff, Inteligence , U S
Learner Autonomy in a Task-Based 3D World and Production
ERIC Educational Resources Information Center
Collentine, Karina
2011-01-01
This study contributes to the research on learner autonomy by examining the relationship between Little's (1991) notions of "independent action" and "decision-making", input, and L2 production in computer-assisted language learning (CALL). Operationalizing "independent action" and "decision-making" with Dam's (1995) definition that focuses on…
Taylor, Andrew T; Garcia, Ernest V
2014-01-01
The goal of artificial intelligence, expert systems, decision support systems and computer assisted diagnosis (CAD) in imaging is the development and implementation of software to assist in the detection and evaluation of abnormalities, to alert physicians to cognitive biases, to reduce intra and inter-observer variability and to facilitate the interpretation of studies at a faster rate and with a higher level of accuracy. These developments are needed to meet the challenges resulting from a rapid increase in the volume of diagnostic imaging studies coupled with a concurrent increase in the number and complexity of images in each patient data. The convergence of an expanding knowledge base and escalating time constraints increases the likelihood of physician errors. Errors are even more likely when physicians interpret low volume studies such as 99mTc-MAG3 diuretic scans where imagers may have had limited training or experience. Decision support systems include neural networks, case-based reasoning, expert systems and statistical systems. iRENEX (renal expert) is an expert system for diuretic renography that uses a set of rules obtained from human experts to analyze a knowledge base of both clinical parameters and quantitative parameters derived from the renogram. Initial studies have shown that the interpretations provided by iRENEX are comparable to the interpretations of a panel of experts. iRENEX provides immediate patient specific feedback at the time of scan interpretation, can be queried to provide the reasons for its conclusions and can be used as an educational tool to teach trainees to better interpret renal scans. iRENEX also has the capacity to populate a structured reporting module and generate a clear and concise impression based on the elements contained in the report; adherence to the procedural and data entry components of the structured reporting module assures and documents procedural competency. Finally, although the focus is CAD applied to diuretic renography, this review offers a window into the rationale, methodology and broader applications of computer assisted diagnosis in medical imaging. PMID:24484751
Simulation of human decision making
Forsythe, J Chris [Sandia Park, NM; Speed, Ann E [Albuquerque, NM; Jordan, Sabina E [Albuquerque, NM; Xavier, Patrick G [Albuquerque, NM
2008-05-06
A method for computer emulation of human decision making defines a plurality of concepts related to a domain and a plurality of situations related to the domain, where each situation is a combination of at least two of the concepts. Each concept and situation is represented in the computer as an oscillator output, and each situation and concept oscillator output is distinguishable from all other oscillator outputs. Information is input to the computer representative of detected concepts, and the computer compares the detected concepts with the stored situations to determine if a situation has occurred.
Computer assisted surgery with 3D robot models and visualisation of the telesurgical action.
Rovetta, A
2000-01-01
This paper deals with the support of virtual reality computer action in the procedures of surgical robotics. Computer support gives a direct representation of the surgical theatre. The modelization of the procedure in course and in development gives a psychological reaction towards safety and reliability. Robots similar to the ones used by the manufacturing industry can be used with little modification as very effective surgical tools. They have high precision, repeatability and are versatile in integrating with the medical instrumentation. Now integrated surgical rooms, with computer and robot-assisted intervention, are operating. The computer is the element for a decision taking aid, and the robot works as a very effective tool.
The River Basin Model: Computer Output. Water Pollution Control Research Series.
ERIC Educational Resources Information Center
Envirometrics, Inc., Washington, DC.
This research report is part of the Water Pollution Control Research Series which describes the results and progress in the control and abatement of pollution in our nation's waters. The River Basin Model described is a computer-assisted decision-making tool in which a number of computer programs simulate major processes related to water use that…
Undergraduate Student Task Group Approach to Complex Problem Solving Employing Computer Programming.
ERIC Educational Resources Information Center
Brooks, LeRoy D.
A project formulated a computer simulation game for use as an instructional device to improve financial decision making. The author constructed a hypothetical firm, specifying its environment, variables, and a maximization problem. Students, assisted by a professor and computer consultants and having access to B5500 and B6700 facilities, held 16…
Computer Network Operations Methodology
2004-03-01
means of their computer information systems. Disrupt - This type of attack focuses on disrupting as “attackers might surreptitiously reprogram enemy...by reprogramming the computers that control distribution within the power grid. A disruption attack introduces disorder and inhibits the effective...between commanders. The use of methodologies is widespread and done subconsciously to assist individuals in decision making. The processes that
Computer-assisted learning and simulation systems in dentistry--a challenge to society.
Welk, A; Splieth, Ch; Wierinck, E; Gilpatrick, R O; Meyer, G
2006-07-01
Computer technology is increasingly used in practical training at universities. However, in spite of their potential, computer-assisted learning (CAL) and computer-assisted simulation (CAS) systems still appear to be underutilized in dental education. Advantages, challenges, problems, and solutions of computer-assisted learning and simulation in dentistry are discussed by means of MEDLINE, open Internet platform searches, and key results of a study among German dental schools. The advantages of computer-assisted learning are seen for example in self-paced and self-directed learning and increased motivation. It is useful for both objective theoretical and practical tests and for training students to handle complex cases. CAL can lead to more structured learning and can support training in evidence-based decision-making. The reasons for the still relatively rare implementation of CAL/CAS systems in dental education include an inability to finance, lack of studies of CAL/CAS, and too much effort required to integrate CAL/CAS systems into the curriculum. To overcome the reasons for the relative low degree of computer technology use, we should strive for multicenter research and development projects monitored by the appropriate national and international scientific societies, so that the potential of computer technology can be fully realized in graduate, postgraduate, and continuing dental education.
NASA Astrophysics Data System (ADS)
Wang, Hongcui; Kawahara, Tatsuya
CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it still remains a challenge to achieve high speech recognition performance, including accurate detection of erroneous utterances by non-native speakers. Conventionally, possible error patterns, based on linguistic knowledge, are added to the lexicon and language model, or the ASR grammar network. However, this approach easily falls in the trade-off of coverage of errors and the increase of perplexity. To solve the problem, we propose a method based on a decision tree to learn effective prediction of errors made by non-native speakers. An experimental evaluation with a number of foreign students learning Japanese shows that the proposed method can effectively generate an ASR grammar network, given a target sentence, to achieve both better coverage of errors and smaller perplexity, resulting in significant improvement in ASR accuracy.
Energy-Aware Computation Offloading of IoT Sensors in Cloudlet-Based Mobile Edge Computing.
Ma, Xiao; Lin, Chuang; Zhang, Han; Liu, Jianwei
2018-06-15
Mobile edge computing is proposed as a promising computing paradigm to relieve the excessive burden of data centers and mobile networks, which is induced by the rapid growth of Internet of Things (IoT). This work introduces the cloud-assisted multi-cloudlet framework to provision scalable services in cloudlet-based mobile edge computing. Due to the constrained computation resources of cloudlets and limited communication resources of wireless access points (APs), IoT sensors with identical computation offloading decisions interact with each other. To optimize the processing delay and energy consumption of computation tasks, theoretic analysis of the computation offloading decision problem of IoT sensors is presented in this paper. In more detail, the computation offloading decision problem of IoT sensors is formulated as a computation offloading game and the condition of Nash equilibrium is derived by introducing the tool of a potential game. By exploiting the finite improvement property of the game, the Computation Offloading Decision (COD) algorithm is designed to provide decentralized computation offloading strategies for IoT sensors. Simulation results demonstrate that the COD algorithm can significantly reduce the system cost compared with the random-selection algorithm and the cloud-first algorithm. Furthermore, the COD algorithm can scale well with increasing IoT sensors.
Enrollment Planning Using Computer Decision Model: A Case Study at Grambling State University.
ERIC Educational Resources Information Center
Ghosh, Kalyan; Lundy, Harold W.
Achieving enrollment goals continues to be a major administrative concern in higher education. Enrollment management can be assisted through the use of computerized planning and forecast models. Although commercially available Markov transition type curve fitting models have been developed and used, a microcomputer-based decision planning model…
ERIC Educational Resources Information Center
Mau, Wei-Cheng; Jepsen, David A.
1992-01-01
Compared decision-making strategies and college major choice among 113 first-year students assigned to Elimination by Aspects Strategy (EBA), Subjective Expected Utility Strategy (SEU), and control groups. "Rational" EBA students scored significantly higher on choice certainty; lower on choice anxiety and career indecision than "rational"…
Plant Closings and Capital Flight: A Computer-Assisted Simulation.
ERIC Educational Resources Information Center
Warner, Stanley; Breitbart, Myrna M.
1989-01-01
A course at Hampshire College was designed to simulate the decision-making environment in which constituencies in a medium-sized city would respond to the closing and relocation of a major corporate plant. The project, constructed as a role simulation with a computer component, is described. (MLW)
Signal Detection Analysis of Computer Enhanced Group Decision Making Strategies
2007-11-01
group decision making. 20 References American Psychological Association (2002). Ethical principles of psychologists and code of conduct. American... Creelman , C. D. (2005). Detection theory: A user’s guide (2nd ed.). Mahwah, NJ: Lawrence Erlbaum. Sorkin, R. D. (1998). Group performance depends on...the majority rule. Psychological Science, 9, 456-463. Sorkin, R. D. (2001). Signal-detection analysis of group decision making. Psychological
Joshi, Vinayak; Agurto, Carla; VanNess, Richard; Nemeth, Sheila; Soliz, Peter; Barriga, Simon
2014-01-01
One of the most important signs of systemic disease that presents on the retina is vascular abnormalities such as in hypertensive retinopathy. Manual analysis of fundus images by human readers is qualitative and lacks in accuracy, consistency and repeatability. Present semi-automatic methods for vascular evaluation are reported to increase accuracy and reduce reader variability, but require extensive reader interaction; thus limiting the software-aided efficiency. Automation thus holds a twofold promise. First, decrease variability while increasing accuracy, and second, increasing the efficiency. In this paper we propose fully automated software as a second reader system for comprehensive assessment of retinal vasculature; which aids the readers in the quantitative characterization of vessel abnormalities in fundus images. This system provides the reader with objective measures of vascular morphology such as tortuosity, branching angles, as well as highlights of areas with abnormalities such as artery-venous nicking, copper and silver wiring, and retinal emboli; in order for the reader to make a final screening decision. To test the efficacy of our system, we evaluated the change in performance of a newly certified retinal reader when grading a set of 40 color fundus images with and without the assistance of the software. The results demonstrated an improvement in reader's performance with the software assistance, in terms of accuracy of detection of vessel abnormalities, determination of retinopathy, and reading time. This system enables the reader in making computer-assisted vasculature assessment with high accuracy and consistency, at a reduced reading time.
From vagueness in medical thought to the foundations of fuzzy reasoning in medical diagnosis.
Seising, Rudolf
2006-11-01
This article delineates a relatively unknown path in the history of medical philosophy and medical diagnosis. It is concerned with the phenomenon of vagueness in the physician's "style of thinking" and with the use of fuzzy sets, systems, and relations with a view to create a model of such reasoning when physicians make a diagnosis. It represents specific features of medical ways of thinking that were mentioned by the Polish physician and philosopher Ludwik Fleck in 1926. The paper links Lotfi Zadeh's work on system theory before the age of fuzzy sets with system-theory concepts in medical philosophy that were introduced by the philosopher Mario Bunge, and with the fuzzy-theoretical analysis of the notions of health, illness, and disease by the Iranian-German physician and philosopher Kazem Sadegh-Zadeh. Some proposals to apply fuzzy sets in medicine were based on a suggestion made by Zadeh: symptoms and diseases are fuzzy in nature and fuzzy sets are feasible to represent these entity classes of medical knowledge. Yet other attempts to use fuzzy sets in medicine were self-contained. The use of this approach contributed to medical decision-making and the development of computer-assisted diagnosis in medicine. With regard to medical philosophy, decision-making, and diagnosis; the framework of fuzzy sets, systems, and relations is very useful to deal with the absence of sharp boundaries of the sets of symptoms, diagnoses, and phenomena of diseases. The foundations of reasoning and computer assistance in medicine were the result of a rapid accumulation of data from medical research. This explosion of knowledge in medicine gave rise to the speculation that computers could be used for the medical diagnosis. Medicine became, to a certain extent, a quantitative science. In the second half of the 20th century medical knowledge started to be stored in computer systems. To assist physicians in medical decision-making and patient care, medical expert systems using the theory of fuzzy sets and relations (such as the Viennese "fuzzy version" of the Computer-Assisted Diagnostic System, CADIAG, which was developed at the end of the 1970s) were constructed. The development of fuzzy relations in medicine and their application in computer-assisted diagnosis show that this fuzzy approach is a framework to deal with the "fuzzy mode of thinking" in medicine.
Kostopoulos, Spiros; Ravazoula, Panagiota; Asvestas, Pantelis; Kalatzis, Ioannis; Xenogiannopoulos, George; Cavouras, Dionisis; Glotsos, Dimitris
2017-06-01
Histopathology image processing, analysis and computer-aided diagnosis have been shown as effective assisting tools towards reliable and intra-/inter-observer invariant decisions in traditional pathology. Especially for cancer patients, decisions need to be as accurate as possible in order to increase the probability of optimal treatment planning. In this study, we propose a new image collection library (HICL-Histology Image Collection Library) comprising 3831 histological images of three different diseases, for fostering research in histopathology image processing, analysis and computer-aided diagnosis. Raw data comprised 93, 116 and 55 cases of brain, breast and laryngeal cancer respectively collected from the archives of the University Hospital of Patras, Greece. The 3831 images were generated from the most representative regions of the pathology, specified by an experienced histopathologist. The HICL Image Collection is free for access under an academic license at http://medisp.bme.teiath.gr/hicl/ . Potential exploitations of the proposed library may span over a board spectrum, such as in image processing to improve visualization, in segmentation for nuclei detection, in decision support systems for second opinion consultations, in statistical analysis for investigation of potential correlations between clinical annotations and imaging findings and, generally, in fostering research on histopathology image processing and analysis. To the best of our knowledge, the HICL constitutes the first attempt towards creation of a reference image collection library in the field of traditional histopathology, publicly and freely available to the scientific community.
NASA Technical Reports Server (NTRS)
Levine, A. L.
1981-01-01
An engineer and a computer expert from Goddard Space Flight Center were assigned to provide technical assistance in the design and installation of a computer assisted system for dispatching and communicating with fire department personnel and equipment in Baltimore City. Primary contributions were in decision making and management processes. The project is analyzed from four perspectives: (1) fire service; (2) technology transfer; (3) public administration; and (5) innovation. The city benefitted substantially from the approach and competence of the NASA personnel. Given the proper conditions, there are distinct advantages in having a nearby Federal laboratory provide assistance to a city on a continuing basis, as is done in the Baltimore Applications Project.
A new decision sciences for complex systems.
Lempert, Robert J
2002-05-14
Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.
The design of aircraft using the decision support problem technique
NASA Technical Reports Server (NTRS)
Mistree, Farrokh; Marinopoulos, Stergios; Jackson, David M.; Shupe, Jon A.
1988-01-01
The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems.
Computer Simulation of a Hardwood Processing Plant
D. Earl Kline; Philip A. Araman
1990-01-01
The overall purpose of this paper is to introduce computer simulation as a decision support tool that can be used to provide managers with timely information. A simulation/animation modeling procedure is demonstrated for wood products manufacuring systems. Simulation modeling techniques are used to assist in identifying and solving problems. Animation is used for...
Liability for Personal Injury Caused by Defective Medical Computer Programs
Brannigan, Vincent M.
1980-01-01
Defective medical computer programs can cause personal injury. Financial responsibility for the injury under tort law will turn on several factors: whether the program is a product or a service, what types of defect exist in the product, and who produced the program. The factors involved in making these decisions are complex, but knowledge of the relevant issues can assist computer personnel in avoiding liability.
Bolef, D
1975-01-01
After ten years of experimentation in computer-assisted cataloging, the Washington University School of Medicine Library has decided to join the Ohio College Library Center network. The history of the library's work preceding this decision is reviewed. The data processing equipment and computers that have permitted librarians to explore different ways of presenting cataloging information are discussed. Certain cataloging processes are facilitated by computer manipulation and printouts, but the intellectual cataloging processes such as descriptive and subject cataloging are not. Networks and shared bibliographic data bases show promise of eliminating the intellectual cataloging for one book by more than one cataloger. It is in this area that future developments can be expected. PMID:1148442
A Computer Assisted Language Analysis System.
ERIC Educational Resources Information Center
Rush, J. E.; And Others
A description is presented of a computer-assisted language analysis system (CALAS) which can serve as a method for isolating and displaying language utterances found in conversation. The purpose of CALAS is stated as being to deal with the question of whether it is possible to detect, isolate, and display information indicative of what is…
Zero-block mode decision algorithm for H.264/AVC.
Lee, Yu-Ming; Lin, Yinyi
2009-03-01
In the previous paper , we proposed a zero-block intermode decision algorithm for H.264 video coding based upon the number of zero-blocks of 4 x 4 DCT coefficients between the current macroblock and the co-located macroblock. The proposed algorithm can achieve significant improvement in computation, but the computation performance is limited for high bit-rate coding. To improve computation efficiency, in this paper, we suggest an enhanced zero-block decision algorithm, which uses an early zero-block detection method to compute the number of zero-blocks instead of direct DCT and quantization (DCT/Q) calculation and incorporates two adequate decision methods into semi-stationary and nonstationary regions of a video sequence. In addition, the zero-block decision algorithm is also applied to the intramode prediction in the P frame. The enhanced zero-block decision algorithm brings out a reduction of average 27% of total encoding time compared to the zero-block decision algorithm.
Sudha, M
2017-09-27
As a recent trend, various computational intelligence and machine learning approaches have been used for mining inferences hidden in the large clinical databases to assist the clinician in strategic decision making. In any target data the irrelevant information may be detrimental, causing confusion for the mining algorithm and degrades the prediction outcome. To address this issue, this study attempts to identify an intelligent approach to assist disease diagnostic procedure using an optimal set of attributes instead of all attributes present in the clinical data set. In this proposed Application Specific Intelligent Computing (ASIC) decision support system, a rough set based genetic algorithm is employed in pre-processing phase and a back propagation neural network is applied in training and testing phase. ASIC has two phases, the first phase handles outliers, noisy data, and missing values to obtain a qualitative target data to generate appropriate attribute reduct sets from the input data using rough computing based genetic algorithm centred on a relative fitness function measure. The succeeding phase of this system involves both training and testing of back propagation neural network classifier on the selected reducts. The model performance is evaluated with widely adopted existing classifiers. The proposed ASIC system for clinical decision support has been tested with breast cancer, fertility diagnosis and heart disease data set from the University of California at Irvine (UCI) machine learning repository. The proposed system outperformed the existing approaches attaining the accuracy rate of 95.33%, 97.61%, and 93.04% for breast cancer, fertility issue and heart disease diagnosis.
Use of handheld computers in clinical practice: a systematic review.
Mickan, Sharon; Atherton, Helen; Roberts, Nia Wyn; Heneghan, Carl; Tilson, Julie K
2014-07-06
Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals' use of handheld computers improve their access to information and support clinical decision making at the point of care? A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study's aim for assessing the impact of handheld computer use. We included seven randomised trials investigating medical or nursing staffs' use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Healthcare professionals' use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes.
Use of handheld computers in clinical practice: a systematic review
2014-01-01
Background Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals’ use of handheld computers improve their access to information and support clinical decision making at the point of care? Methods A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study’s aim for assessing the impact of handheld computer use. Results We included seven randomised trials investigating medical or nursing staffs’ use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Conclusion Healthcare professionals’ use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes. PMID:24998515
Glassman, E Katelyn; Hughes, Michelle L
2013-01-01
Current cochlear implants (CIs) have telemetry capabilities for measuring the electrically evoked compound action potential (ECAP). Neural Response Telemetry (Cochlear) and Neural Response Imaging (Advanced Bionics [AB]) can measure ECAP responses across a range of stimulus levels to obtain an amplitude growth function. Software-specific algorithms automatically mark the leading negative peak, N1, and the following positive peak/plateau, P2, and apply linear regression to estimate ECAP threshold. Alternatively, clinicians may apply expert judgments to modify the peak markers placed by the software algorithms, or use visual detection to identify the lowest level yielding a measurable ECAP response. The goals of this study were to: (1) assess the variability between human and computer decisions for (a) marking N1 and P2 and (b) determining linear-regression threshold (LRT) and visual-detection threshold (VDT); and (2) compare LRT and VDT methods within and across human- and computer-decision methods. ECAP amplitude-growth functions were measured for three electrodes in each of 20 ears (10 Cochlear Nucleus® 24RE/CI512, and 10 AB CII/90K). LRT, defined as the current level yielding an ECAP with zero amplitude, was calculated for both computer- (C-LRT) and human-picked peaks (H-LRT). VDT, defined as the lowest level resulting in a measurable ECAP response, was also calculated for both computer- (C-VDT) and human-picked peaks (H-VDT). Because Neural Response Imaging assigns peak markers to all waveforms but does not include waveforms with amplitudes less than 20 μV in its regression calculation, C-VDT for AB subjects was defined as the lowest current level yielding an amplitude of 20 μV or more. Overall, there were significant correlations between human and computer decisions for peak-marker placement, LRT, and VDT for both manufacturers (r = 0.78-1.00, p < 0.001). For Cochlear devices, LRT and VDT correlated equally well for both computer- and human-picked peaks (r = 0.98-0.99, p < 0.001), which likely reflects the well-defined Neural Response Telemetry algorithm and the lower noise floor in the 24RE and CI512 devices. For AB devices, correlations between LRT and VDT for both peak-picker methods were weaker than for Cochlear devices (r = 0.69-0.85, p < 0.001), which likely reflect the higher noise floor of the system. Disagreement between computer and human decisions regarding the presence of an ECAP response occurred for 5 % of traces for Cochlear devices and 2.1 % of traces for AB devices. Results indicate that human and computer peak-picking methods can be used with similar accuracy for both Cochlear and AB devices. Either C-VDT or C-LRT can be used with equal confidence for Cochlear 24RE and CI512 recipients because both methods are strongly correlated with human decisions. However, for AB devices, greater variability exists between different threshold-determination methods. This finding should be considered in the context of using ECAP measures to assist with programming CIs.
Decision making technical support study for the US Army's Chemical Stockpile Disposal Program
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feldman, D.L.; Dobson, J.E.
1990-08-01
This report examines the adequacy of current command and control systems designed to make timely decisions that would enable sufficient warning and protective response to an accident at the Edgewood area of Aberdeen Proving Ground (APG), Maryland, and at Pine Bluff Arsenal (PBA), Arkansas. Institutional procedures designed to facilitate rapid accident assessment, characterization, warning, notification, and response after the onset of an emergency and computer-assisted decision-making aids designed to provide salient information to on- and-off-post emergency responders are examined. The character of emergency decision making at APG and PBA, as well as potential needs for improvements to decision-making practices, procedures,more » and automated decision-support systems (ADSSs), are described and recommendations are offered to guide equipment acquisition and improve on- and off-post command and control relationships. We recommend that (1) a continued effort be made to integrate on- and off-post command control, and decision-making procedures to permit rapid decision making; (2) the pathways for alert and notification among on- and off-post officials be improved and that responsibilities and chain of command among off-post agencies be clarified; (3) greater attention be given to organizational and social context factors that affect the adequacy of response and the likelihood that decision-making systems will work as intended; and (4) faster improvements be made to on-post ADSSs being developed at APG and PBA, which hold considerable promise for depicting vast amounts of information. Phased development and procurement of computer-assisted decision-making tools should be undertaken to balance immediate needs against available resources and to ensure flexibility, equity among sites, and compatibility among on- and off-post systems. 112 refs., 6 tabs.« less
Self-evaluation of decision-making: A general Bayesian framework for metacognitive computation.
Fleming, Stephen M; Daw, Nathaniel D
2017-01-01
People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a "second-order" inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one's own actions to metacognitive judgments. In addition, the model provides insight into why subjects' metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation
2017-01-01
People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a “second-order” inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one’s own actions to metacognitive judgments. In addition, the model provides insight into why subjects’ metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. PMID:28004960
Strategic Imagination: The Lost Dimension of Strategic Studies.
1984-09-01
the advent of computer technology brought about not only an increased usage of gaming techniques, but also broadened the spectrum of prob- lems and...direct relevance for the use of experts as advisors in decision-making, especially in areas of broad or long-range policy formulation. It is useful for...and the Anti Submarine Warfare trainer in Norfolk. 5. Computer Assisted Games The advent of computers opened many new possibili- ties for scenario
Computer-Assisted Instruction: Decision Handbook.
1985-04-01
to feelings of " depersonalization " or "dehumanization." The approach is to document investigations of attitudes toward CBI held by students and...utilized within a computer-based training system that includes management of student progress, training resources, testing, and instructional materials...training time. As compared to programmed texts and workbookl, students were more attentive and stayed on task. The attentiveness to PLATO materials
ERIC Educational Resources Information Center
FALL, CHARLES R.
THIS DOCUMENT CONCLUDES THAT INSTRUCTION BY COMPUTER-BASED RESOURCE UNITS CAN FACILITATE LEARNING AND PROVIDE THE INSTRUCTOR WITH VALUABLE ASSISTANCE. BY PRE-PLANNING THE TEACHING-LEARNING SITUATION, RESOURCE UNITS CAN FREE THE INSTRUCTOR FOR DECISION-MAKING TASKS. RESOURCE UNITS CAN ALSO PROVIDE APPROPRIATE LEARNING GOALS AND STUDY GUIDES TO EACH…
Target Information Processing: A Joint Decision and Estimation Approach
2012-03-29
ground targets ( track - before - detect ) using computer cluster and graphics processing unit. Estimation and filtering theory is one of the most important...targets ( track - before - detect ) using computer cluster and graphics processing unit. Estimation and filtering theory is one of the most important
Ji, Yanqing; Ying, Hao; Farber, Margo S.; Yen, John; Dews, Peter; Miller, Richard E.; Massanari, R. Michael
2014-01-01
Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is of great importance. The current approach to postmarketing surveillance primarily relies on spontaneous reporting. It is a passive surveillance system and limited by gross underreporting (<10% reporting rate), latency, and inconsistent reporting. We propose a novel team-based intelligent agent software system approach for proactively monitoring and detecting potential ADRs of interest using electronic patient records. We designed such a system and named it ADRMonitor. The intelligent agents, operating on computers located in different places, are capable of continuously and autonomously collaborating with each other and assisting the human users (e.g., the food and drug administration (FDA), drug safety professionals, and physicians). The agents should enhance current systems and accelerate early ADR identification. To evaluate the performance of the ADRMonitor with respect to the current spontaneous reporting approach, we conducted simulation experiments on identification of ADR signal pairs (i.e., potential links between drugs and apparent adverse reactions) under various conditions. The experiments involved over 275 000 simulated patients created on the basis of more than 1000 real patients treated by the drug cisapride that was on the market for seven years until its withdrawal by the FDA in 2000 due to serious ADRs. Healthcare professionals utilizing the spontaneous reporting approach and the ADRMonitor were separately simulated by decision-making models derived from a general cognitive decision model called fuzzy recognition-primed decision (RPD) model that we recently developed. The quantitative simulation results show that 1) the number of true ADR signal pairs detected by the ADRMonitor is 6.6 times higher than that by the spontaneous reporting strategy; 2) the ADR detection rate of the ADRMonitor agents with even moderate decision-making skills is five times higher than that of spontaneous reporting; and 3) as the number of patient cases increases, ADRs could be detected significantly earlier by the ADRMonitor. PMID:20007038
NASA Astrophysics Data System (ADS)
Lieberman, Robert; Kwong, Heston; Liu, Brent; Huang, H. K.
2009-02-01
The chest x-ray radiological features of tuberculosis patients are well documented, and the radiological features that change in response to successful pharmaceutical therapy can be followed with longitudinal studies over time. The patients can also be classified as either responsive or resistant to pharmaceutical therapy based on clinical improvement. We have retrospectively collected time series chest x-ray images of 200 patients diagnosed with tuberculosis receiving the standard pharmaceutical treatment. Computer algorithms can be created to utilize image texture features to assess the temporal changes in the chest x-rays of the tuberculosis patients. This methodology provides a framework for a computer-assisted detection (CAD) system that may provide physicians with the ability to detect poor treatment response earlier in pharmaceutical therapy. Early detection allows physicians to respond with more timely treatment alternatives and improved outcomes. Such a system has the potential to increase treatment efficacy for millions of patients each year.
Assistive lesion-emphasis system: an assistive system for fundus image readers
Rangrej, Samrudhdhi B.; Sivaswamy, Jayanthi
2017-01-01
Abstract. Computer-assisted diagnostic (CAD) tools are of interest as they enable efficient decision-making in clinics and the screening of diseases. The traditional approach to CAD algorithm design focuses on the automated detection of abnormalities independent of the end-user, who can be an image reader or an expert. We propose a reader-centric system design wherein a reader’s attention is drawn to abnormal regions in a least-obtrusive yet effective manner, using saliency-based emphasis of abnormalities and without altering the appearance of the background tissues. We present an assistive lesion-emphasis system (ALES) based on the above idea, for fundus image-based diabetic retinopathy diagnosis. Lesion-saliency is learnt using a convolutional neural network (CNN), inspired by the saliency model of Itti and Koch. The CNN is used to fine-tune standard low-level filters and learn high-level filters for deriving a lesion-saliency map, which is then used to perform lesion-emphasis via a spatially variant version of gamma correction. The proposed system has been evaluated on public datasets and benchmarked against other saliency models. It was found to outperform other saliency models by 6% to 30% and boost the contrast-to-noise ratio of lesions by more than 30%. Results of a perceptual study also underscore the effectiveness and, hence, the potential of ALES as an assistive tool for readers. PMID:28560245
Bae, Dae Kyung; Song, Sang Jun; Kim, Kang Il; Hur, Dong; Jeong, Ho Yeon
2016-03-01
The purpose of the present study was to compare the clinical and radiographic results and survival rates between computer-assisted and conventional closing wedge high tibial osteotomies (HTOs). Data from a consecutive cohort comprised of 75 computer-assisted HTOs and 75 conventional HTOs were retrospectively reviewed. The Knee Society knee and function scores, Hospital for Special Surgery (HSS) score and femorotibial angle (FTA) were compared between the two groups. Survival rates were also compared with procedure failure. The knee and function scores at one year postoperatively were slightly better in the computer-assisted group than those in conventional group (90.1 vs. 86.1) (82.0 vs. 76.0). The HSS scores at one year postoperatively were slightly better for the computer-assisted HTOs than those of conventional HTOs (89.5 vs. 81.8). The inlier of the postoperative FTA was wider in the computer-assisted group than that in the conventional HTO group (88.0% vs. 58.7%), and mean postoperative FTA was greater in the computer-assisted group that in the conventional HTO group (valgus 9.0° vs. valgus 7.6°, p<0.001). The five- and 10-year survival rates were 97.1% and 89.6%, respectively. No difference was detected in nine-year survival rates (p=0.369) between the two groups, although the clinical and radiographic results were better in the computer-assisted group that those in the conventional HTO group. Mid-term survival rates did not differ between computer-assisted and conventional HTOs. A comparative analysis of longer-term survival rate is required to demonstrate the long-term benefit of computer-assisted HTO. III. Copyright © 2015 Elsevier B.V. All rights reserved.
2017-05-01
Patient requests for transfer of embryos with genetic anomalies linked to serious health-affecting disorders detected in preimplantation testing are rare but do exist. This Opinion sets out the possible rationales for a provider's decision to assist or decline to assist in such transfers. The Committee concludes in most clinical cases it is ethically permissible to assist or decline to assist in transferring such embryos. In circumstances in which a child is highly likely to be born with a life-threatening condition that causes severe and early debility with no possibility of reasonable function, provider transfer of such embryos is ethically problematic and highly discouraged. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.
The use of wireless laptop computers for computer-assisted learning in pharmacokinetics.
Munar, Myrna Y; Singh, Harleen; Belle, Donna; Brackett, Carolyn C; Earle, Sandra B
2006-02-15
To implement computer-assisted learning workshops into pharmacokinetics courses in a doctor of pharmacy (PharmD) program. Workshops were designed for students to utilize computer software programs on laptop computers to build pharmacokinetic models to predict drug concentrations resulting from various dosage regimens. In addition, students were able to visualize through graphing programs how altering different parameters changed drug concentration-time curves. Surveys were conducted to measure students' attitudes toward computer technology before and after implementation. Finally, traditional examinations were used to evaluate student learning. Doctor of pharmacy students responded favorably to the use of wireless laptop computers in problem-based pharmacokinetic workshops. Eighty-eight percent (n = 61/69) and 82% (n = 55/67) of PharmD students completed surveys before and after computer implementation, respectively. Prior to implementation, 95% of students agreed that computers would enhance learning in pharmacokinetics. After implementation, 98% of students strongly agreed (p < 0.05) that computers enhanced learning. Examination results were significantly higher after computer implementation (89% with computers vs. 84% without computers; p = 0.01). Implementation of wireless laptop computers in a pharmacokinetic course enabled students to construct their own pharmacokinetic models that could respond to changing parameters. Students had greater comprehension and were better able to interpret results and provide appropriate recommendations. Computer-assisted pharmacokinetic techniques can be powerful tools when making decisions about drug therapy.
The Use of Wireless Laptop Computers for Computer-Assisted Learning in Pharmacokinetics
Munar, Myrna Y.; Singh, Harleen; Belle, Donna; Brackett, Carolyn C.; Earle, Sandra B.
2006-01-01
Objective To implement computer-assisted learning workshops into pharmacokinetics courses in a doctor of pharmacy (PharmD) program. Design Workshops were designed for students to utilize computer software programs on laptop computers to build pharmacokinetic models to predict drug concentrations resulting from various dosage regimens. In addition, students were able to visualize through graphing programs how altering different parameters changed drug concentration-time curves. Surveys were conducted to measure students’ attitudes toward computer technology before and after implementation. Finally, traditional examinations were used to evaluate student learning. Assessment Doctor of pharmacy students responded favorably to the use of wireless laptop computers in problem-based pharmacokinetic workshops. Eighty-eight percent (n = 61/69) and 82% (n = 55/67) of PharmD students completed surveys before and after computer implementation, respectively. Prior to implementation, 95% of students agreed that computers would enhance learning in pharmacokinetics. After implementation, 98% of students strongly agreed (p < 0.05) that computers enhanced learning. Examination results were significantly higher after computer implementation (89% with computers vs. 84% without computers; p = 0.01). Conclusion Implementation of wireless laptop computers in a pharmacokinetic course enabled students to construct their own pharmacokinetic models that could respond to changing parameters. Students had greater comprehension and were better able to interpret results and provide appropriate recommendations. Computer-assisted pharmacokinetic techniques can be powerful tools when making decisions about drug therapy. PMID:17136147
Pattern recognition for passive polarimetric data using nonparametric classifiers
NASA Astrophysics Data System (ADS)
Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.
2005-08-01
Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.
Electronic decision support in general practice. What's the hold up?
Liaw, S T; Schattner, P
2003-11-01
The uptake of computers in Australian general practice has been for administrative use and prescribing, but the development of electronic decision support (EDS) has been particularly slow. Therefore, computers are not being used to their full potential in assisting general practitioners to care for their patients. This article examines current barriers to EDS in general practice and possible strategies to increase its uptake. Barriers to the uptake of EDS include a lack of a business case, shifting of costs for data collection and management to the clinician, uncertainty about the optimal level of decision support, lack of technical and semantic standards, and resistance to EDS use by the time conscious GP. There is a need for a more strategic and attractive incentives program, greater national coordination, and more effective collaboration between government, the computer industry and the medical profession if current inertia is to be overcome.
Texture classification of lung computed tomography images
NASA Astrophysics Data System (ADS)
Pheng, Hang See; Shamsuddin, Siti M.
2013-03-01
Current development of algorithms in computer-aided diagnosis (CAD) scheme is growing rapidly to assist the radiologist in medical image interpretation. Texture analysis of computed tomography (CT) scans is one of important preliminary stage in the computerized detection system and classification for lung cancer. Among different types of images features analysis, Haralick texture with variety of statistical measures has been used widely in image texture description. The extraction of texture feature values is essential to be used by a CAD especially in classification of the normal and abnormal tissue on the cross sectional CT images. This paper aims to compare experimental results using texture extraction and different machine leaning methods in the classification normal and abnormal tissues through lung CT images. The machine learning methods involve in this assessment are Artificial Immune Recognition System (AIRS), Naive Bayes, Decision Tree (J48) and Backpropagation Neural Network. AIRS is found to provide high accuracy (99.2%) and sensitivity (98.0%) in the assessment. For experiments and testing purpose, publicly available datasets in the Reference Image Database to Evaluate Therapy Response (RIDER) are used as study cases.
ERIC Educational Resources Information Center
Mitzel, Harold E.
In cooperation with the United States Navy, this project was undertaken to examine the feasibility of computer assisted instruction in clinical malaria recognition, to train a small group of Naval personnel in techniques of creating and presenting such material, and to evaluate the course by giving it to a representative sample of Naval medical…
From Resource-Adaptive Navigation Assistance to Augmented Cognition
NASA Astrophysics Data System (ADS)
Zimmer, Hubert D.; Münzer, Stefan; Baus, Jörg
In an assistance scenario, a computer provides purposive information supporting a human user in an everyday situation. Wayfinding with navigation assistance is a prototypical assistance scenario. The present chapter analyzes the interplay of the resources of the assistance system and the resources of the user. The navigation assistance system provides geographic knowledge, positioning information, route planning, spatial overview information, and route commands at decision points. The user's resources encompass spatial knowledge, spatial abilities and visuo-spatial working memory, orientation strategies, and cultural habit. Flexible adaptations of the assistance system to available resources of the user are described, taking different wayfinding goals, situational constraints, and individual differences into account. Throughout the chapter, the idea is pursued that the available resources of the user should be kept active.
Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data
in ’t Veen, Johannes C.C.M.; Dekhuijzen, P.N. Richard; van Heijst, Ellen; Kocks, Janwillem W.H.; Muilwijk-Kroes, Jacqueline B.; Chavannes, Niels H.; van der Molen, Thys
2016-01-01
The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years) with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD) service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215). Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS) patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%). Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool. PMID:27730177
Development and evaluation of learning module on clinical decision-making in Prosthodontics.
Deshpande, Saee; Lambade, Dipti; Chahande, Jayashree
2015-01-01
Best practice strategies for helping students learn the reasoning skills of problem solving and critical thinking (CT) remain a source of conjecture, particularly with regard to CT. The dental education literature is fundamentally devoid of research on the cognitive components of clinical decision-making. This study was aimed to develop and evaluate the impact of blended learning module on clinical decision-making skills of dental graduates for planning prosthodontics rehabilitation. An interactive teaching module consisting of didactic lectures on clinical decision-making and a computer-assisted case-based treatment planning software was developed Its impact on cognitive knowledge gain in clinical decision-making was evaluated using an assessment involving problem-based multiple choice questions and paper-based case scenarios. Mean test scores were: Pretest (17 ± 1), posttest 1 (21 ± 2) and posttest 2 (43 ± 3). Comparison of mean scores was done with one-way ANOVA test. There was overall significant difference in between mean scores at all the three points (P < 0.001). A pair-wise comparison of mean scores was done with Bonferroni test. The mean difference is significant at the 0.05 level. The pair-wise comparison shows that posttest 2 score is significantly higher than posttest 1 and posttest 1 is significantly higher than pretest that is, pretest 2 > posttest 1 > pretest. Blended teaching methods employing didactic lectures on the clinical decision-making as well as computer assisted case-based learning can be used to improve quality of clinical decision-making in prosthodontic rehabilitation for dental graduates.
A Genetic Algorithm Approach to Motion Sensor Placement in Smart Environments.
Thomas, Brian L; Crandall, Aaron S; Cook, Diane J
2016-04-01
Smart environments and ubiquitous computing technologies hold great promise for a wide range of real world applications. The medical community is particularly interested in high quality measurement of activities of daily living. With accurate computer modeling of older adults, decision support tools may be built to assist care providers. One aspect of effectively deploying these technologies is determining where the sensors should be placed in the home to effectively support these end goals. This work introduces and evaluates a set of approaches for generating sensor layouts in the home. These approaches range from the gold standard of human intuition-based placement to more advanced search algorithms, including Hill Climbing and Genetic Algorithms. The generated layouts are evaluated based on their ability to detect activities while minimizing the number of needed sensors. Sensor-rich environments can provide valuable insights about adults as they go about their lives. These sensors, once in place, provide information on daily behavior that can facilitate an aging-in-place approach to health care.
A Genetic Algorithm Approach to Motion Sensor Placement in Smart Environments
Thomas, Brian L.; Crandall, Aaron S.; Cook, Diane J.
2016-01-01
Smart environments and ubiquitous computing technologies hold great promise for a wide range of real world applications. The medical community is particularly interested in high quality measurement of activities of daily living. With accurate computer modeling of older adults, decision support tools may be built to assist care providers. One aspect of effectively deploying these technologies is determining where the sensors should be placed in the home to effectively support these end goals. This work introduces and evaluates a set of approaches for generating sensor layouts in the home. These approaches range from the gold standard of human intuition-based placement to more advanced search algorithms, including Hill Climbing and Genetic Algorithms. The generated layouts are evaluated based on their ability to detect activities while minimizing the number of needed sensors. Sensor-rich environments can provide valuable insights about adults as they go about their lives. These sensors, once in place, provide information on daily behavior that can facilitate an aging-in-place approach to health care. PMID:27453810
Computer-assisted diagnosis of melanoma.
Fuller, Collin; Cellura, A Paul; Hibler, Brian P; Burris, Katy
2016-03-01
The computer-assisted diagnosis of melanoma is an exciting area of research where imaging techniques are combined with diagnostic algorithms in an attempt to improve detection and outcomes for patients with skin lesions suspicious for malignancy. Once an image has been acquired, it undergoes a processing pathway which includes preprocessing, enhancement, segmentation, feature extraction, feature selection, change detection, and ultimately classification. Practicality for everyday clinical use remains a vital question. A successful model must obtain results that are on par or outperform experienced dermatologists, keep costs at a minimum, be user-friendly, and be time efficient with high sensitivity and specificity. ©2015 Frontline Medical Communications.
NASA Astrophysics Data System (ADS)
Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.
2017-02-01
We present a three-step approach based on the commercial VIAPIX® module for road traffic sign recognition and identification. Firstly, detection in a scene of all objects having characteristics of traffic signs is performed. This is followed by a first-level recognition based on correlation which consists in making a comparison between each detected object with a set of reference images of a database. Finally, a second level of identification allows us to confirm or correct the previous identification. In this study, we perform a correlation-based analysis by combining and adapting the Vander Lugt correlator with the nonlinear joint transformation correlator (JTC). Of particular significance, this approach permits to make a reliable decision on road traffic sign identification. We further discuss a robust scheme allowing us to track a detected road traffic sign in a video sequence for the purpose of increasing the decision performance of our system. This approach can have broad practical applications in the maintenance and rehabilitation of transportation infrastructure, or for drive assistance.
Fusion Imaging: A Novel Staging Modality in Testis Cancer
Sterbis, Joseph R.; Rice, Kevin R.; Javitt, Marcia C.; Schenkman, Noah S.; Brassell, Stephen A.
2010-01-01
Objective: Computed tomography and chest radiographs provide the standard imaging for staging, treatment, and surveillance of testicular germ cell neoplasms. Positron emission tomography has recently been utilized for staging, but is somewhat limited in its ability to provide anatomic localization. Fusion imaging combines the metabolic information provided by positron emission tomography with the anatomic precision of computed tomography. To the best of our knowledge, this represents the first study of the effectiveness using fusion imaging in evaluation of patients with testis cancer. Methods: A prospective study of 49 patients presenting to Walter Reed Army Medical Center with testicular cancer from 2003 to 2009 was performed. Fusion imaging was compared with conventional imaging, tumor markers, pathologic results, and clinical follow-up. Results: There were 14 true positives, 33 true negatives, 1 false positive, and 1 false negative. Sensitivity, specificity, positive predictive value, and negative predictive value were 93.3, 97.0, 93.3, and 97.0% respectively. In 11 patient scenarios, fusion imaging differed from conventional imaging. Utility was found in superior lesion detection compared to helical computed tomography due to anatomical/functional image co-registration, detection of micrometastasis in lymph nodes (pathologic nodes < 1cm), surveillance for recurrence post-chemotherapy, differentiating fibrosis from active disease in nodes < 2.5cm, and acting as a quality assurance measure to computed tomography alone. Conclusions: In addition to demonstrating a sensitivity and specificity comparable or superior to conventional imaging, fusion imaging shows promise in providing additive data that may assist in clinical decision-making. PMID:21103077
Fusion imaging: a novel staging modality in testis cancer.
Sterbis, Joseph R; Rice, Kevin R; Javitt, Marcia C; Schenkman, Noah S; Brassell, Stephen A
2010-11-05
Computed tomography and chest radiographs provide the standard imaging for staging, treatment, and surveillance of testicular germ cell neoplasms. Positron emission tomography has recently been utilized for staging, but is somewhat limited in its ability to provide anatomic localization. Fusion imaging combines the metabolic information provided by positron emission tomography with the anatomic precision of computed tomography. To the best of our knowledge, this represents the first study of the effectiveness using fusion imaging in evaluation of patients with testis cancer. A prospective study of 49 patients presenting to Walter Reed Army Medical Center with testicular cancer from 2003 to 2009 was performed. Fusion imaging was compared with conventional imaging, tumor markers, pathologic results, and clinical follow-up. There were 14 true positives, 33 true negatives, 1 false positive, and 1 false negative. Sensitivity, specificity, positive predictive value, and negative predictive value were 93.3, 97.0, 93.3, and 97.0% respectively. In 11 patient scenarios, fusion imaging differed from conventional imaging. Utility was found in superior lesion detection compared to helical computed tomography due to anatomical/functional image co-registration, detection of micrometastasis in lymph nodes (pathologic nodes < 1cm), surveillance for recurrence post-chemotherapy, differentiating fibrosis from active disease in nodes < 2.5cm, and acting as a quality assurance measure to computed tomography alone. In addition to demonstrating a sensitivity and specificity comparable or superior to conventional imaging, fusion imaging shows promise in providing additive data that may assist in clinical decision-making.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-03-06
...: Computer Matching Program AGENCY: Treasury Inspector General for Tax Administration, Treasury. ACTION... Internal Revenue Service (IRS) concerning the conduct of TIGTA's computer matching program. DATES... INFORMATION: TIGTA's computer matching program assists in the detection and deterrence of fraud, waste, and...
An Investigation Into the Navy Public Works Centers Specific Work Service Processing Problems.
1980-12-01
demonstrated. These computations are from Navy Area Audit Service reports or PWC and NAVFACENGCOM reports. Number One-time Annual Personnel 3,553...study, all of the endorsements, and a Navy Audit Service audit of the cost analysis, the CNO makes the final consolidation decision. With a decision to...organizations to which local activities turn for environmental issue assistance such as noise, water and air polution , airfield encroachment, local
Systematic Analysis of the Decision Rules of Traditional Chinese Medicine
Bin-Rong, Ma; Xi-Yuan, Jiang; Su-Ming, Liso; Huai-ning, Zhu; Xiu-ru, Lin
1981-01-01
Chinese traditional medicine has evolved over many centuries, and has accumulated a body of observed relationships between symptoms, signs and prognoses, and the efficacy of alternative treatments and prescriptions. With the assistance of a computer-based clinical data base for recording the diagnostic and therapeutic practice of skilled practitioners of Chinese traditional medicine, a systematic program is being conducted to identify and define the clinical decision-making rules that underlie current practice.
PitScan: Computer-Assisted Feature Detection
NASA Astrophysics Data System (ADS)
Wagner, R. V.; Robinson, M. S.
2018-04-01
We developed PitScan to assist in searching the very large LROC image dataset for pits — unusual <200m wide vertical-walled holes in the Moon's surface. PitScan reduces analysts' workload by pre-filtering images to identify possible pits.
NASA Astrophysics Data System (ADS)
Gur, David
2018-03-01
We tested whether a case based CADe scheme, developed only on negatively interpreted screening mammograms, has predictive value for cancer detection during subsequent screening and how this approach may affect radiologists' performances when alerting them to a small subset ( 15%) of exams on which radiologists tend to miss cancers. A series of six parameters case based CADe schemes, using 200 negative mammograms (800 images 100 women with breast cancer at subsequent screening and 100 women who remained negative), carefully matched by age and breast density, were optimized. CADe alone schemes performed at AUC=0.68 (+/- 0.01). Five radiologists and 4 residents interpreted the same cases and performed at AUC =0.71 (experienced radiologists) and AUC= 0.61 (residents). With the "CADe warnings" shown to the interpreters only if they did not recall one of 24 highest CADe scoring cases, assisted performance of radiologists and residents respectively, were 0.71 and 0.63 (p>0.05). However, when the CADe alone performance was raised to an AUC=0.78, by artificially increasing the number of possible warnings from 16 to 24, radiologists' performances significantly improved from an AUC of 0.68 to 0.72 (p<0.05). In conclusion, the use case based information other than breast density could highlight a small fraction of women whose cancers are more likely to be missed by radiologists and later detected during subsequent mammograms, thereby, leading to an assisted approach that improves radiologists' performances. However, to be effective, the performance of the CADe alone should be substantially higher (e.g. ΔAUC >=0.07) than that of the un-assisted radiologist.
ERIC Educational Resources Information Center
Godsall, R. A.
1974-01-01
A management simulation course has been designed by Dunchurch Industrial Staff College (DISC) that is management oriented rather than marketing oriented. The computer assisted program has been successful in allowing managers to experience immediately the effects of their decisions and also to experience each other's jobs and problems. (DS)
Stefanović, Stefica Cerjan; Bolanča, Tomislav; Luša, Melita; Ukić, Sime; Rogošić, Marko
2012-02-24
This paper describes the development of ad hoc methodology for determination of inorganic anions in oilfield water, since their composition often significantly differs from the average (concentration of components and/or matrix). Therefore, fast and reliable method development has to be performed in order to ensure the monitoring of desired properties under new conditions. The method development was based on computer assisted multi-criteria decision making strategy. The used criteria were: maximal value of objective functions used, maximal robustness of the separation method, minimal analysis time, and maximal retention distance between two nearest components. Artificial neural networks were used for modeling of anion retention. The reliability of developed method was extensively tested by the validation of performance characteristics. Based on validation results, the developed method shows satisfactory performance characteristics, proving the successful application of computer assisted methodology in the described case study. Copyright © 2011 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Ren, Feixiang; Huang, Jinsheng; Terauchi, Mutsuhiro; Jiang, Ruyi; Klette, Reinhard
A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on). In this paper, we propose a new platform for the implementation of lane detection, which is based on a mobile phone (the iPhone). Due to physical limitations of the iPhone w.r.t. memory and computing power, a simple and efficient lane detection algorithm using a Hough transform is developed and implemented on the iPhone, as existing algorithms developed based on the PC platform are not suitable for mobile phone devices (currently). Experiments of the lane detection algorithm are made both on PC and on iPhone.
Parasuraman, Raja; de Visser, Ewart; Lin, Ming-Kuan; Greenwood, Pamela M.
2012-01-01
Computerized aiding systems can assist human decision makers in complex tasks but can impair performance when they provide incorrect advice that humans erroneously follow, a phenomenon known as “automation bias.” The extent to which people exhibit automation bias varies significantly and may reflect inter-individual variation in the capacity of working memory and the efficiency of executive function, both of which are highly heritable and under dopaminergic and noradrenergic control in prefrontal cortex. The dopamine beta hydroxylase (DBH) gene is thought to regulate the differential availability of dopamine and norepinephrine in prefrontal cortex. We therefore examined decision-making performance under imperfect computer aiding in 100 participants performing a simulated command and control task. Based on two single nucleotide polymorphism (SNPs) of the DBH gene, −1041 C/T (rs1611115) and 444 G/A (rs1108580), participants were divided into groups of low and high DBH enzyme activity, where low enzyme activity is associated with greater dopamine relative to norepinephrine levels in cortex. Compared to those in the high DBH enzyme activity group, individuals in the low DBH enzyme activity group were more accurate and speedier in their decisions when incorrect advice was given and verified automation recommendations more frequently. These results indicate that a gene that regulates relative prefrontal cortex dopamine availability, DBH, can identify those individuals who are less susceptible to bias in using computerized decision-aiding systems. PMID:22761865
Multi-Sector Sustainability Browser (MSSB) User Manual: A ...
EPA’s Sustainable and Healthy Communities (SHC) Research Program is developing methodologies, resources, and tools to assist community members and local decision makers in implementing policy choices that facilitate sustainable approaches in managing their resources affecting the built environment, natural environment, and human health. In order to assist communities and decision makers in implementing sustainable practices, EPA is developing computer-based systems including models, databases, web tools, and web browsers to help communities decide upon approaches that support their desired outcomes. Communities need access to resources that will allow them to achieve their sustainability objectives through intelligent decisions in four key sustainability areas: • Land Use • Buildings and Infrastructure • Transportation • Materials Management (i.e., Municipal Solid Waste [MSW] processing and disposal) The Multi-Sector Sustainability Browser (MSSB) is designed to support sustainable decision-making for communities, local and regional planners, and policy and decision makers. Document is an EPA Technical Report, which is the user manual for the Multi-Sector Sustainability Browser (MSSB) tool. The purpose of the document is to provide basic guidance on use of the tool for users
The analysis of the pilot's cognitive and decision processes
NASA Technical Reports Server (NTRS)
Curry, R. E.
1975-01-01
Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.
Traffic light detection and intersection crossing using mobile computer vision
NASA Astrophysics Data System (ADS)
Grewei, Lynne; Lagali, Christopher
2017-05-01
The solution for Intersection Detection and Crossing to support the development of blindBike an assisted biking system for the visually impaired is discussed. Traffic light detection and intersection crossing are key needs in the task of biking. These problems are tackled through the use of mobile computer vision, in the form of a mobile application on an Android phone. This research builds on previous Traffic Light detection algorithms with a focus on efficiency and compatibility on a resource-limited platform. Light detection is achieved through blob detection algorithms utilizing training data to detect patterns of Red, Green and Yellow in complex real world scenarios where multiple lights may be present. Also, issues of obscurity and scale are addressed. Safe Intersection crossing in blindBike is also discussed. This module takes a conservative "assistive" technology approach. To achieve this blindBike use's not only the Android device but, an external bike cadence Bluetooth/Ant enabled sensor. Real world testing results are given and future work is discussed.
A soft kinetic data structure for lesion border detection.
Kockara, Sinan; Mete, Mutlu; Yip, Vincent; Lee, Brendan; Aydin, Kemal
2010-06-15
The medical imaging and image processing techniques, ranging from microscopic to macroscopic, has become one of the main components of diagnostic procedures to assist dermatologists in their medical decision-making processes. Computer-aided segmentation and border detection on dermoscopic images is one of the core components of diagnostic procedures and therapeutic interventions for skin cancer. Automated assessment tools for dermoscopic images have become an important research field mainly because of inter- and intra-observer variations in human interpretations. In this study, a novel approach-graph spanner-for automatic border detection in dermoscopic images is proposed. In this approach, a proximity graph representation of dermoscopic images in order to detect regions and borders in skin lesion is presented. Graph spanner approach is examined on a set of 100 dermoscopic images whose manually drawn borders by a dermatologist are used as the ground truth. Error rates, false positives and false negatives along with true positives and true negatives are quantified by digitally comparing results with manually determined borders from a dermatologist. The results show that the highest precision and recall rates obtained to determine lesion boundaries are 100%. However, accuracy of assessment averages out at 97.72% and borders errors' mean is 2.28% for whole dataset.
Designing and Implementation of River Classification Assistant Management System
NASA Astrophysics Data System (ADS)
Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan
2018-03-01
In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.
1982-05-01
Raiffa (831, LaValle [891, and other books on decision analysis. 4.2 Risk Attitudes Much recent research has focused on the investigation of various risk...Issacs, G.L., Hamer, R., Chen, J., Chuang, D., Woodworth, G., Molenaar , I., Lewis C., and Libby, D., Manual for the Computer-Assisted Data Analysis (CADA
The Collins Center Update. Volume 5, Issue 3, April-June 2003
2003-06-01
Crisis and Instability Forecasting Capabilities (Dr. Sean O’Brien) students from the other Senior Level Colleges in a free play , computer-assisted war...dynamic free play environment. The exercise developments in response to the participants’ actions and decisions, not by scripts or a master
Ambient Assisted Living spaces validation by services and devices simulation.
Fernández-Llatas, Carlos; Mocholí, Juan Bautista; Sala, Pilar; Naranjo, Juan Carlos; Pileggi, Salvatore F; Guillén, Sergio; Traver, Vicente
2011-01-01
The design of Ambient Assisted Living (AAL) products is a very demanding challenge. AAL products creation is a complex iterative process which must accomplish exhaustive prerequisites about accessibility and usability. In this process the early detection of errors is crucial to create cost-effective systems. Computer-assisted tools can suppose a vital help to usability designers in order to avoid design errors. Specifically computer simulation of products in AAL environments can be used in all the design phases to support the validation. In this paper, a computer simulation tool for supporting usability designers in the creation of innovative AAL products is presented. This application will benefit their work saving time and improving the final system functionality.
The multimedia computer for office-based patient education: a systematic review.
Wofford, James L; Smith, Edward D; Miller, David P
2005-11-01
Use of the multimedia computer for education is widespread in schools and businesses, and yet computer-assisted patient education is rare. In order to explore the potential use of computer-assisted patient education in the office setting, we performed a systematic review of randomized controlled trials (search date April 2004 using MEDLINE and Cochrane databases). Of the 26 trials identified, outcome measures included clinical indicators (12/26, 46.1%), knowledge retention (12/26, 46.1%), health attitudes (15/26, 57.7%), level of shared decision-making (5/26, 19.2%), health services utilization (4/26, 17.6%), and costs (5/26, 19.2%), respectively. Four trials targeted patients with breast cancer, but the clinical issues were otherwise diverse. Reporting of the testing of randomization (76.9%) and appropriate analysis of main effect variables (70.6%) were more common than reporting of a reliable randomization process (35.3%), blinding of outcomes assessment (17.6%), or sample size definition (29.4%). We concluded that the potential for improving the efficiency of the office through computer-assisted patient education has been demonstrated, but better proof of the impact on clinical outcomes is warranted before this strategy is accepted in the office setting.
Kuhl, Mitchell; Beimel, Claudia
2016-10-01
The goal of this study was to evaluate the ability of a novel computer assisted surgery system to guide ideal placement of a lag screw during cephalomedullary nailing and then accurately measure the tip-apex distance (TAD) measurement intraoperatively. Retrospective case review. Level II trauma hospital. The initial 98 consecutive clinical cases treated with a cephalomedullary nail in conjunction with a novel computer assisted surgery system were retrospectively reviewed. A novel computer assisted surgery system was utilized to enhance lag screw placement during cephalomedullary nailing procedures. The computer assisted surgery system calculates the TAD intraoperatively after final lag screw placement. The ideal TAD was considered to be within a range of 5mm-20mm. The ability of the computer assisted surgery system (CASS) to assist in placement of a lag screw within the ideal TAD was evaluated. Intraoperative TAD measurements provided by the computer assisted surgery system were then compared to standard postoperative TAD measurements on PACS (picture archiving and communication system) images to determine whether these measurements are equivalent. 79 cases (80.6%) were available with complete information for a retrospective review. All cases had CASS TAD and PACS TAD measurements >5mm and<20mm. In addition, no significant difference could be detected between the intraoperative CASS TAD and the postoperative PACS TAD (p=0.374, Wilcoxon Test; p=0.174, paired T-Test). A cut-out rate of 0% was observed in all patients who were treated with CASS in this case series (95% CI: 0 - 3.01%). The novel computer assisted surgery system tested here is an effective and reliable adjunct that can be utilized for optimal lag screw placement in cephalomedullary nailing procedures. The computer assisted surgery system provides an accurate intraoperative TAD measurement that is equivalent to the standard postoperative measurement utilizing PACS images. Therapeutic Level IV. Copyright © 2016 Elsevier Ltd. All rights reserved.
Progress in analysis of computed tomography (CT) images of hardwood logs for defect detection
Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt
2003-01-01
This paper addresses the problem of automatically detecting internal defects in logs using computed tomography (CT) images. The overall purpose is to assist in breakdown optimization. Several studies have shown that the commercial value of resulting boards can be increased substantially if defect locations are known in advance, and if this information is used to make...
Decision theory, reinforcement learning, and the brain.
Dayan, Peter; Daw, Nathaniel D
2008-12-01
Decision making is a core competence for animals and humans acting and surviving in environments they only partially comprehend, gaining rewards and punishments for their troubles. Decision-theoretic concepts permeate experiments and computational models in ethology, psychology, and neuroscience. Here, we review a well-known, coherent Bayesian approach to decision making, showing how it unifies issues in Markovian decision problems, signal detection psychophysics, sequential sampling, and optimal exploration and discuss paradigmatic psychological and neural examples of each problem. We discuss computational issues concerning what subjects know about their task and how ambitious they are in seeking optimal solutions; we address algorithmic topics concerning model-based and model-free methods for making choices; and we highlight key aspects of the neural implementation of decision making.
Building a Foreign Military Sales Construction Delivery Strategy Decision Support System
1991-09-01
DSS, formulates it into a computer model and produces solutions using information and expert heuristics. Using the Expert Systeic Process to Build a DSS...computer model . There are five stages in the development of an expert system. They are: 1) Identify and characterize the important aspects of the problem...and Steven A. Hidreth. U.S. Security Assistance: The Political Process. Massachusetts: Heath and Company, 1985. 19. Guirguis , Amir A., Program
76 FR 61717 - Government-Owned Inventions; Availability for Licensing
Federal Register 2010, 2011, 2012, 2013, 2014
2011-10-05
... computer science based technology that may provide the capability of detecting untoward events such as... is comprised of a dedicated computer server that executes specially designed software with input data... computer assisted clinical ordering. J Biomed Inform. 2003 Feb-Apr;36(1-2):4-22. [PMID 14552843...
Miller, R A
2010-01-01
The INTERNIST-1/Quick Medical Reference (QMR) diagnostic decision support project spans four decades, from 1971-onward. This paper describes the history of the project and details insights gained of relevance to the general clinical and informatics communities.
Individual Differences in Learner Controlled CAI.
ERIC Educational Resources Information Center
Judd, Wilson A.; And Others
Two assumptions in support of learner-controlled computer-assisted instruction (CAI) are that (1) instruction administered under learner control will be less aversive than if administered under program control, and (2) the student is sufficiently aware of his learning state to make, in most instances, his own instructional decisions. Some 130…
Meteorological Decision Assistance.
1981-08-01
500 for labor and materials. The most economical course of action can be determined by computing the cost/loss ratio (C/L) and comparing it to the...interest, a clima - tology of these parameters, the impact of these parameters on the customer’s mission, and the techniques for assessing the probability of
Guidelines for the Development of Computerized Student Information Systems.
ERIC Educational Resources Information Center
Armes, Nancy, Ed.; And Others
Designed to provide guidelines for the development of computerized student information systems, this report raises policy issues and questions to be resolved at the campus level and describes a variety of computer-generated reports and records that can assist in educational decision making and planning. Introductory material discusses the…
76 FR 78286 - Collection of Information Under Review by Office of Management and Budget
Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-16
..., between 9 a.m. and 5 p.m., Monday through Friday, except Federal holidays. OIRA posts its decisions on.... Coast Guard, Acting Assistant Commandant for Command, Control, Communications, Computers and Information... DEPARTMENT OF HOMELAND SECURITY Coast Guard [USCG-2011-0902] Collection of Information Under...
Segmentation-assisted detection of dirt impairments in archived film sequences.
Ren, Jinchang; Vlachos, Theodore
2007-04-01
In this correspondence, a novel segmentation-assisted method for film-dirt detection is proposed. We exploit the fact that film dirt manifests in the spatial domain as a cluster of connected pixels whose intensity differs substantially from that of its neighborhood, and we employ a segmentation-based approach to identify this type of structure. A key feature of our approach is the computation of a measure of confidence attached to detected dirt regions, which can be utilized for performance fine tuning. Another important feature of our algorithm is the avoidance of the computational complexity associated with motion estimation. Our experimental framework benefits from the availability of manually derived as well as objective ground-truth data obtained using infrared scanning. Our results demonstrate that the proposed method compares favorably with standard spatial, temporal, and multistage median-filtering approaches and provides efficient and robust detection for a wide variety of test materials.
Computers in medicine: liability issues for physicians.
Hafner, A W; Filipowicz, A B; Whitely, W P
1989-07-01
Physicians routinely use computers to store, access, and retrieve medical information. As computer use becomes even more widespread in medicine, failure to utilize information systems may be seen as a violation of professional custom and lead to findings of professional liability. Even when a technology is not widespread, failure to incorporate it into medical practice may give rise to liability if the technology is accessible to the physician and reduces risk to the patient. Improvement in the availability of medical information sources imposes a greater burden on the physician to keep current and to obtain informed consent from patients. To routinely perform computer-assisted literature searches for informed consent and diagnosis is 'good medicine'. Clinical and diagnostic applications of computer technology now include computer-assisted decision making with the aid of sophisticated databases. Although such systems will expand the knowledge base and competence of physicians, malfunctioning software raises a major liability question. Also, complex computer-driven technology is used in direct patient care. Defective or improperly used hardware or software can lead to patient injury, thus raising additional complicated questions of professional liability and product liability.
Quality metrics for sensor images
NASA Technical Reports Server (NTRS)
Ahumada, AL
1993-01-01
Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.
Jing, Xueping; Zheng, Xiujuan; Song, Shaoli; Liu, Kai
2017-12-01
Glomerular filtration rate (GFR), which can be estimated by Gates method with dynamic kidney single photon emission computed tomography (SPECT) imaging, is a key indicator of renal function. In this paper, an automatic computer tomography (CT)-assisted detection method of kidney region of interest (ROI) is proposed to achieve the objective and accurate GFR calculation. In this method, the CT coronal projection image and the enhanced SPECT synthetic image are firstly generated and registered together. Then, the kidney ROIs are delineated using a modified level set algorithm. Meanwhile, the background ROIs are also obtained based on the kidney ROIs. Finally, the value of GFR is calculated via Gates method. Comparing with the clinical data, the GFR values estimated by the proposed method were consistent with the clinical reports. This automatic method can improve the accuracy and stability of kidney ROI detection for GFR calculation, especially when the kidney function has been severely damaged.
Tourassi, Georgia D; Harrawood, Brian; Singh, Swatee; Lo, Joseph Y; Floyd, Carey E
2007-01-01
The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrieval precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tourassi, Georgia D.; Harrawood, Brian; Singh, Swatee
The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrievalmore » precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.« less
Discharge Chamber Primary Electron Modeling Activities in Three-Dimensions
NASA Technical Reports Server (NTRS)
Steuber, Thomas J.
2004-01-01
Designing discharge chambers for ion thrusters involves many geometric configuration decisions. Various decisions will impact discharge chamber performance with respect to propellant utilization efficiency, ion production costs, and grid lifetime. These hardware design decisions can benefit from the assistance of computational modeling. Computational modeling for discharge chambers has been limited to two-dimensional codes that leveraged symmetry for interpretation into three-dimensional analysis. This paper presents model development activities towards a three-dimensional discharge chamber simulation to aid discharge chamber design decisions. Specifically, of the many geometric configuration decisions toward attainment of a worthy discharge chamber, this paper focuses on addressing magnetic circuit considerations with a three-dimensional discharge chamber simulation as a tool. With this tool, candidate discharge chamber magnetic circuit designs can be analyzed computationally to gain insight into factors that may influence discharge chamber performance such as: primary electron loss width in magnetic cusps, cathode tip position with respect to the low magnetic field volume, definition of a low magnetic field region, and maintenance of a low magnetic field region across the grid span. Corroborating experimental data will be obtained from mockup hardware tests. Initially, simulated candidate magnetic circuit designs will resemble previous successful thruster designs. To provide opportunity to improve beyond previous performance benchmarks, off-design modifications will be simulated and experimentally tested.
Ray, Midge N; Houston, Thomas K; Yu, Feliciano B; Menachemi, Nir; Maisiak, Richard S; Allison, Jeroan J; Berner, Eta S
2006-01-01
The authors developed and evaluated a rating scale, the Attitudes toward Handheld Decision Support Software Scale (H-DSS), to assess physician attitudes about handheld decision support systems. The authors conducted a prospective assessment of psychometric characteristics of the H-DSS including reliability, validity, and responsiveness. Participants were 82 Internal Medicine residents. A higher score on each of the 14 five-point Likert scale items reflected a more positive attitude about handheld DSS. The H-DSS score is the mean across the fourteen items. Attitudes toward the use of the handheld DSS were assessed prior to and six months after receiving the handheld device. Cronbach's Alpha was used to assess internal consistency reliability. Pearson correlations were used to estimate and detect significant associations between scale scores and other measures (validity). Paired sample t-tests were used to test for changes in the mean attitude scale score (responsiveness) and for differences between groups. Internal consistency reliability for the scale was alpha = 0.73. In testing validity, moderate correlations were noted between the attitude scale scores and self-reported Personal Digital Assistant (PDA) usage in the hospital (correlation coefficient = 0.55) and clinic (0.48), p < 0.05 for both. The scale was responsive, in that it detected the expected increase in scores between the two administrations (3.99 (s.d. = 0.35) vs. 4.08, (s.d. = 0.34), p < 0.005). The authors' evaluation showed that the H-DSS scale was reliable, valid, and responsive. The scale can be used to guide future handheld DSS development and implementation.
Warmann, Steven W; Schenk, Andrea; Schaefer, Juergen F; Ebinger, Martin; Blumenstock, Gunnar; Tsiflikas, Ilias; Fuchs, Joerg
2016-11-01
In complex malignant pediatric liver tumors there is an ongoing discussion regarding surgical strategy; for example, primary organ transplantation versus extended resection in hepatoblastoma involving 3 or 4 sectors of the liver. We evaluated the possible role of computer-assisted surgery planning in children with complex hepatic tumors. Between May 2004 and March 2016, 24 Children with complex liver tumors underwent standard multislice helical CT scan or MRI scan at our institution. Imaging data were processed using the software assistant LiverAnalyzer (Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany). Results were provided as Portable Document Format (PDF) with embedded interactive 3-dimensional surface mesh models. Median age of patients was 33months. Diagnoses were hepatoblastoma (n=14), sarcoma (n=3), benign parenchyma alteration (n=2), as well as hepatocellular carcinoma, rhabdoid tumor, focal nodular hyperplasia, hemangioendothelioma, or multiple hepatic metastases of a pancreas carcinoma (each n=1). Volumetry of liver segments identified remarkable variations and substantial aberrances from the Couinaud classification. Computer-assisted surgery planning was used to determine surgical strategies in 20/24 children; this was especially relevant in tumors affecting 3 or 4 liver sectors. Primary liver transplantation could be avoided in 12 of 14 hepaoblastoma patients who theoretically were candidates for this approach. Computer-assisted surgery planning substantially contributed to the decision for surgical strategies in children with complex hepatic tumors. This tool possibly allows determination of specific surgical procedures such as extended surgical resection instead of primary transplantation in certain conditions. Copyright © 2016. Published by Elsevier Inc.
Unobtrusive monitoring of computer interactions to detect cognitive status in elders.
Jimison, Holly; Pavel, Misha; McKanna, James; Pavel, Jesse
2004-09-01
The U.S. has experienced a rapid growth in the use of computers by elders. E-mail, Web browsing, and computer games are among the most common routine activities for this group of users. In this paper, we describe techniques for unobtrusively monitoring naturally occurring computer interactions to detect sustained changes in cognitive performance. Researchers have demonstrated the importance of the early detection of cognitive decline. Users over the age of 75 are at risk for medically related cognitive problems and confusion, and early detection allows for more effective clinical intervention. In this paper, we present algorithms for inferring a user's cognitive performance using monitoring data from computer games and psychomotor measurements associated with keyboard entry and mouse movement. The inferences are then used to classify significant performance changes, and additionally, to adapt computer interfaces with tailored hints and assistance when needed. These methods were tested in a group of elders in a residential facility.
The paper discusses a computer-based decision support tool that has been developed to assist local governments in evaluating the cost and environmental performance of integrated municipal solid waste (MSW) managment systems. ongoing case studies of the tool at the local level are...
A Group-Decision Approach for Evaluating Educational Web Sites
ERIC Educational Resources Information Center
Hwang, Gwo-Jen; Huanga, Tony C. K.; Tseng, Judy C. R.
2004-01-01
With the advent of network technologies, many educational web sites have been developed to assist students in the learning of subjects on computer networks. However, without proper aid, students may have difficulty in selecting appropriate web sites, that are of benefit to them; hence, studying, evaluating and recommending educational web sites…
Does the Medium Really Matter in L2 Development? The Validity of Call Research Designs
ERIC Educational Resources Information Center
Cerezo, Luis; Baralt, Melissa; Suh, Bo-Ram; Leow, Ronald P.
2014-01-01
Currently, an increasing number of educational institutions are redefining second/foreign language (L2) classrooms by enhancing--or even replacing--traditional face-to-face (FTF) instruction with computer-assisted language learning (CALL). However, are these curricular decisions supported by research? Overall, a cursory review of empirical studies…
NASA Astrophysics Data System (ADS)
Bravos, Angelo; Hill, Howard; Choca, James; Bresolin, Linda B.; Bresolin, Michael J.
1986-03-01
Computer technology is rapidly becoming an inseparable part of many health science specialties. Recently, a new area of computer technology, namely Artificial Intelligence, has been applied toward assisting the medical experts in their diagnostic and therapeutic decision making process. MOODIS is an experimental diagnostic expert system which assists Psychiatry specialists in diagnosing human Mood Disorders, better known as Affective Disorders. Its diagnostic methodology is patterned after MDX, a diagnostic expert system developed at LAIR (Laboratory for Artificial Intelligence Research) of Ohio State University. MOODIS is implemented in CSRL (Conceptual Structures Representation Language) also developed at LAIR. This paper describes MOODIS in terms of conceptualization and requirements, and discusses why the MDX approach and CSRL were chosen.
Barlough, J E; Jacobson, R H; Sorresso, G P; Lynch, T J; Scott, F W
1986-07-01
A total of 2238 feline serum samples submitted to the New York State Diagnostic Laboratory over a 1-year period were tested for the presence of coronavirus antibodies, using the computer-assisted, kinetics-based enzyme-linked immunosorbent assay (KELA). Cats from which sera were obtained were categorized by sex, age, breed, and disease status, and variations in mean antibody titers for different sub-classifications within each category were analyzed by computerized statistical analysis. As expected, higher mean antibody titers were recorded for cats with feline infectious peritonitis, and for cats with a recent history of possible coronavirus exposure. However, an unexpected inverse relationship between coronavirus antibody titer and age was also found. Certain cattery-oriented pure breeds appeared to have higher mean antibody titers, because their sample populations contained a higher percentage of younger cats and cats of unknown age-groups which, over-all, had higher mean titers. Taken together, the data substantiated the efficacy of the computer-assisted KELA for routine detection of serum coronavirus antibodies in cats.
Medical sieve: a cognitive assistant for radiologists and cardiologists
NASA Astrophysics Data System (ADS)
Syeda-Mahmood, T.; Walach, E.; Beymer, D.; Gilboa-Solomon, F.; Moradi, M.; Kisilev, P.; Kakrania, D.; Compas, C.; Wang, H.; Negahdar, R.; Cao, Y.; Baldwin, T.; Guo, Y.; Gur, Y.; Rajan, D.; Zlotnick, A.; Rabinovici-Cohen, S.; Ben-Ari, R.; Guy, Amit; Prasanna, P.; Morey, J.; Boyko, O.; Hashoul, S.
2016-03-01
Radiologists and cardiologists today have to view large amounts of imaging data relatively quickly leading to eye fatigue. Further, they have only limited access to clinical information relying mostly on their visual interpretation of imaging studies for their diagnostic decisions. In this paper, we present Medical Sieve, an automated cognitive assistant for radiologists and cardiologists designed to help in their clinical decision-making. The sieve is a clinical informatics system that collects clinical, textual and imaging data of patients from electronic health records systems. It then analyzes multimodal content to detect anomalies if any, and summarizes the patient record collecting all relevant information pertinent to a chief complaint. The results of anomaly detection are then fed into a reasoning engine which uses evidence from both patient-independent clinical knowledge and large-scale patient-driven similar patient statistics to arrive at potential differential diagnosis to help in clinical decision making. In compactly summarizing all relevant information to the clinician per chief complaint, the system still retains links to the raw data for detailed review providing holistic summaries of patient conditions. Results of clinical studies in the domains of cardiology and breast radiology have already shown the promise of the system in differential diagnosis and imaging studies summarization.
Boger, Jennifer; Mihailidis, Alex
2011-01-01
A person's ability to be independent is dependent on his or her overall health, mobility, and ability to complete activities of daily living. Intelligent assistive technologies (IATs) are devices that incorporate context into their decision-making process, which enables them to provide customised and dynamic assistance in an appropriate manner. IATs have tremendous potential to support people with cognitive impairments as they can be used to support many facets of well-being; from augmenting memory and decision making tasks to providing autonomous and early detection of possible changes in health. This paper presents IATs that are currently in development in the research community to support tasks that can be impacted by compromised cognition. While they are not yet ready for the general public, these devices showcase the capabilities of technologies one can expect to see in the consumer marketplace in the near future.
Biomedical wellness challenges and opportunities
NASA Astrophysics Data System (ADS)
Tangney, John F.
2012-06-01
The mission of ONR's Human and Bioengineered Systems Division is to direct, plan, foster, and encourage Science and Technology in cognitive science, computational neuroscience, bioscience and bio-mimetic technology, social/organizational science, training, human factors, and decision making as related to future Naval needs. This paper highlights current programs that contribute to future biomedical wellness needs in context of humanitarian assistance and disaster relief. ONR supports fundamental research and related technology demonstrations in several related areas, including biometrics and human activity recognition; cognitive sciences; computational neurosciences and bio-robotics; human factors, organizational design and decision research; social, cultural and behavioral modeling; and training, education and human performance. In context of a possible future with automated casualty evacuation, elements of current science and technology programs are illustrated.
Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt; Philip A. Araman
2005-01-01
This paper describes recent progress in the analysis of computed tomography (CT) images of hardwood logs. The long-term goal of the work is to develop a system that is capable of autonomous (or semiautonomous) detection of internal defects, so that log breakdown decisions can be optimized based on defect locations. The problem is difficult because wood exhibits large...
Pneumothorax detection in chest radiographs using convolutional neural networks
NASA Astrophysics Data System (ADS)
Blumenfeld, Aviel; Konen, Eli; Greenspan, Hayit
2018-02-01
This study presents a computer assisted diagnosis system for the detection of pneumothorax (PTX) in chest radiographs based on a convolutional neural network (CNN) for pixel classification. Using a pixel classification approach allows utilization of the texture information in the local environment of each pixel while training a CNN model on millions of training patches extracted from a relatively small dataset. The proposed system uses a pre-processing step of lung field segmentation to overcome the large variability in the input images coming from a variety of imaging sources and protocols. Using a CNN classification, suspected pixel candidates are extracted within each lung segment. A postprocessing step follows to remove non-physiological suspected regions and noisy connected components. The overall percentage of suspected PTX area was used as a robust global decision for the presence of PTX in each lung. The system was trained on a set of 117 chest x-ray images with ground truth segmentations of the PTX regions. The system was tested on a set of 86 images and reached diagnosis accuracy of AUC=0.95. Overall preliminary results are promising and indicate the growing ability of CAD based systems to detect findings in medical imaging on a clinical level accuracy.
Ideal AFROC and FROC observers.
Khurd, Parmeshwar; Liu, Bin; Gindi, Gene
2010-02-01
Detection of multiple lesions in images is a medically important task and free-response receiver operating characteristic (FROC) analyses and its variants, such as alternative FROC (AFROC) analyses, are commonly used to quantify performance in such tasks. However, ideal observers that optimize FROC or AFROC performance metrics have not yet been formulated in the general case. If available, such ideal observers may turn out to be valuable for imaging system optimization and in the design of computer aided diagnosis techniques for lesion detection in medical images. In this paper, we derive ideal AFROC and FROC observers. They are ideal in that they maximize, amongst all decision strategies, the area, or any partial area, under the associated AFROC or FROC curve. Calculation of observer performance for these ideal observers is computationally quite complex. We can reduce this complexity by considering forms of these observers that use false positive reports derived from signal-absent images only. We also consider a Bayes risk analysis for the multiple-signal detection task with an appropriate definition of costs. A general decision strategy that minimizes Bayes risk is derived. With particular cost constraints, this general decision strategy reduces to the decision strategy associated with the ideal AFROC or FROC observer.
[Basic concept in computer assisted surgery].
Merloz, Philippe; Wu, Hao
2006-03-01
To investigate application of medical digital imaging systems and computer technologies in orthopedics. The main computer-assisted surgery systems comprise the four following subcategories. (1) A collection and recording process for digital data on each patient, including preoperative images (CT scans, MRI, standard X-rays), intraoperative visualization (fluoroscopy, ultrasound), and intraoperative position and orientation of surgical instruments or bone sections (using 3D localises). Data merging based on the matching of preoperative imaging (CT scans, MRI, standard X-rays) and intraoperative visualization (anatomical landmarks, or bone surfaces digitized intraoperatively via 3D localiser; intraoperative ultrasound images processed for delineation of bone contours). (2) In cases where only intraoperative images are used for computer-assisted surgical navigation, the calibration of the intraoperative imaging system replaces the merged data system, which is then no longer necessary. (3) A system that provides aid in decision-making, so that the surgical approach is planned on basis of multimodal information: the interactive positioning of surgical instruments or bone sections transmitted via pre- or intraoperative images, display of elements to guide surgical navigation (direction, axis, orientation, length and diameter of a surgical instrument, impingement, etc. ). And (4) A system that monitors the surgical procedure, thereby ensuring that the optimal strategy defined at the preoperative stage is taken into account. It is possible that computer-assisted orthopedic surgery systems will enable surgeons to better assess the accuracy and reliability of the various operative techniques, an indispensable stage in the optimization of surgery.
Anayama, Takashi; Hirohashi, Kentaro; Miyazaki, Ryohei; Okada, Hironobu; Kawamoto, Nobutaka; Yamamoto, Marino; Sato, Takayuki; Orihashi, Kazumasa
2018-01-12
Minimally invasive video-assisted thoracoscopic surgery for small-sized pulmonary nodules is challenging, and image-guided preoperative localisation is required. Near-infrared indocyanine green fluorescence is capable of deep tissue penetration and can be distinguished regardless of the background colour of the lung; thus, indocyanine green has great potential for use as a near-infrared fluorescent marker in video-assisted thoracoscopic surgery. Thirty-seven patients with small-sized pulmonary nodules, who were scheduled to undergo video-assisted thoracoscopic wedge resection, were enrolled in this study. A mixture of diluted indocyanine green and iopamidol was injected into the lung parenchyma as a marker, using either computed tomography-guided percutaneous or bronchoscopic injection techniques. Indications and limitations of the percutaneous and bronchoscopic injection techniques for marking nodules with indocyanine green fluorescence were examined and compared. In the computed tomography-guided percutaneous injection group (n = 15), indocyanine green fluorescence was detected in 15/15 (100%) patients by near-infrared thoracoscopy. A small pneumothorax occurred in 3/15 (20.0%) patients, and subsequent marking was unsuccessful after a pneumothorax occurred. In the bronchoscopic injection group (n = 22), indocyanine green fluorescence was detected in 21/22 (95.5%) patients. In 6 patients who underwent injection marking at 2 different lesion sites, 5/6 (83.3%) markers were successfully detected. Either computed tomography-guided percutaneous or bronchoscopic injection techniques can be used to mark pulmonary nodules with indocyanine green fluorescence. Indocyanine green is a safe and easily detectable fluorescent marker for video-assisted thoracoscopic surgery. Furthermore, the bronchoscopic injection approach enables surgeons to mark multiple lesion areas with less risk of causing a pneumothorax. UMIN-CTR R000027833 accepted by ICMJE. Registered 5 January 2013.
Computer-assisted instruction: a library service for the community teaching hospital.
McCorkel, J; Cook, V
1986-04-01
This paper reports on five years of experience with computer-assisted instruction (CAI) at Winthrop-University Hospital, a major affiliate of the SUNY at Stony Brook School of Medicine. It compares CAI programs available from Ohio State University and Massachusetts General Hospital (accessed by telephone and modem), and software packages purchased from the Health Sciences Consortium (MED-CAPS) and Scientific American (DISCOTEST). The comparison documents one library's experience of the cost of these programs and the use made of them by medical students, house staff, and attending physicians. It describes the space allocated for necessary equipment, as well as the marketing of CAI. Finally, in view of the decision of the National Board of Medical Examiners to administer the Part III examination on computer (the so-called CBX) starting in 1988, the paper speculates on the future importance of CAI in the community teaching hospital.
Acoustic emission data assisted process monitoring.
Yen, Gary G; Lu, Haiming
2002-07-01
Gas-liquid two-phase flows are widely used in the chemical industry. Accurate measurements of flow parameters, such as flow regimes, are the key of operating efficiency. Due to the interface complexity of a two-phase flow, it is very difficult to monitor and distinguish flow regimes on-line and real time. In this paper we propose a cost-effective and computation-efficient acoustic emission (AE) detection system combined with artificial neural network technology to recognize four major patterns in an air-water vertical two-phase flow column. Several crucial AE parameters are explored and validated, and we found that the density of acoustic emission events and ring-down counts are two excellent indicators for the flow pattern recognition problems. Instead of the traditional Fair map, a hit-count map is developed and a multilayer Perceptron neural network is designed as a decision maker to describe an approximate transmission stage of a given two-phase flow system.
NASA Astrophysics Data System (ADS)
Mehrtash, Alireza; Sedghi, Alireza; Ghafoorian, Mohsen; Taghipour, Mehdi; Tempany, Clare M.; Wells, William M.; Kapur, Tina; Mousavi, Parvin; Abolmaesumi, Purang; Fedorov, Andriy
2017-03-01
Prostate cancer (PCa) remains a leading cause of cancer mortality among American men. Multi-parametric magnetic resonance imaging (mpMRI) is widely used to assist with detection of PCa and characterization of its aggressiveness. Computer-aided diagnosis (CADx) of PCa in MRI can be used as clinical decision support system to aid radiologists in interpretation and reporting of mpMRI. We report on the development of a convolution neural network (CNN) model to support CADx in PCa based on the appearance of prostate tissue in mpMRI, conducted as part of the SPIE-AAPM-NCI PROSTATEx challenge. The performance of different combinations of mpMRI inputs to CNN was assessed and the best result was achieved using DWI and DCE-MRI modalities together with the zonal information of the finding. On the test set, the model achieved an area under the receiver operating characteristic curve of 0.80.
Visual saliency-based fast intracoding algorithm for high efficiency video coding
NASA Astrophysics Data System (ADS)
Zhou, Xin; Shi, Guangming; Zhou, Wei; Duan, Zhemin
2017-01-01
Intraprediction has been significantly improved in high efficiency video coding over H.264/AVC with quad-tree-based coding unit (CU) structure from size 64×64 to 8×8 and more prediction modes. However, these techniques cause a dramatic increase in computational complexity. An intracoding algorithm is proposed that consists of perceptual fast CU size decision algorithm and fast intraprediction mode decision algorithm. First, based on the visual saliency detection, an adaptive and fast CU size decision method is proposed to alleviate intraencoding complexity. Furthermore, a fast intraprediction mode decision algorithm with step halving rough mode decision method and early modes pruning algorithm is presented to selectively check the potential modes and effectively reduce the complexity of computation. Experimental results show that our proposed fast method reduces the computational complexity of the current HM to about 57% in encoding time with only 0.37% increases in BD rate. Meanwhile, the proposed fast algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.
Education's Role in Determining New Industrial Plant Locations: A State Study.
ERIC Educational Resources Information Center
Baker, Richard A.; Wilmoth, James N.
1989-01-01
Reports results of a study to determine if education, in general, and factors related to vocational education, in particular, were considered in location decisions in a southern state. Analyzes data collected through on-site interviews with chief executive officers of 25 plants chosen randomly from results of a computer-assisted sort procedure.…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-06-24
... will discuss, make recommendations, and vote on premarket approval application for MelaFind, sponsored by MELA Sciences, Inc. MelaFind is a non-invasive computer vision system intended to assist in the... characteristics of melanoma, before a final decision to biopsy has been rendered. MelaFind acquires and displays...
ERIC Educational Resources Information Center
Peng, Hsinyi; Chuang, Po-Ya; Hwang, Gwo-Jen; Chu, Hui-Chun; Wu, Ting-Ting; Huang, Shu-Xian
2009-01-01
Researchers have conducted various studies on applying wireless communication and ubiquitous computing technologies to education, so that the technologies can provide learners and educators with more active and adaptive support. This study proposes a Ubiquitous Performance-support System (UPSS) that can facilitate the seamless use of powerful new…
Choosing a Microcomputer for Use as a Teaching Aid.
ERIC Educational Resources Information Center
Visniesky, Cheryl; Hocking, Joan
A step-by-step guide to the selection of a microcomputer system is provided for educators having made the decision to implement computer-assisted instruction. The first step is to clarify reasons for using a microcomputer rather than conventional instructional materials. Next, the degree of use (e.g., types of courses and number of departments…
A university/industry panel will report on the progress and findings of a fivesteve-year project funded by the US Environmental Protection Agency. The project's end product will be a Web-based, 3D computer-simulated residential environment with a decision support system to assist...
The Evolutionary Development of CAI Hardware.
ERIC Educational Resources Information Center
Stifle, John E.
After six years of research in computer assisted instruction (CAI) using PLATO III, a decision was made at the University of Illinois to develop a larger system as a national CAI resource. This document describes the design specifications and problems in the development of PLATO IV, a system which is capable of accomodating up to 4,000 terminals…
Kappanayil, Mahesh; Koneti, Nageshwara Rao; Kannan, Rajesh R; Kottayil, Brijesh P; Kumar, Krishna
2017-01-01
Three-dimensional. (3D) printing is an innovative manufacturing process that allows computer-assisted conversion of 3D imaging data into physical "printouts" Healthcare applications are currently in evolution. The objective of this study was to explore the feasibility and impact of using patient-specific 3D-printed cardiac prototypes derived from high-resolution medical imaging data (cardiac magnetic resonance imaging/computed tomography [MRI/CT]) on surgical decision-making and preoperative planning in selected cases of complex congenital heart diseases (CHDs). Five patients with complex CHD with previously unresolved management decisions were chosen. These included two patients with complex double-outlet right ventricle, two patients with criss-cross atrioventricular connections, and one patient with congenitally corrected transposition of great arteries with pulmonary atresia. Cardiac MRI was done for all patients, cardiac CT for one; specific surgical challenges were identified. Volumetric data were used to generate patient-specific 3D models. All cases were reviewed along with their 3D models, and the impact on surgical decision-making and preoperative planning was assessed. Accurate life-sized 3D cardiac prototypes were successfully created for all patients. The models enabled radically improved 3D understanding of anatomy, identification of specific technical challenges, and precise surgical planning. Augmentation of existing clinical and imaging data by 3D prototypes allowed successful execution of complex surgeries for all five patients, in accordance with the preoperative planning. 3D-printed cardiac prototypes can radically assist decision-making, planning, and safe execution of complex congenital heart surgery by improving understanding of 3D anatomy and allowing anticipation of technical challenges.
NASA Astrophysics Data System (ADS)
Cong, Runmin; Han, Ping; Li, Chongyi; He, Jiaji; Zhang, Zaiji
2016-09-01
Targets of interest are different in various applications in which manmade targets, such as aircraft, ships, and buildings, are given more attention. Manmade target extraction methods using synthetic aperture radar (SAR) images are designed in response to various demands, which include civil uses, business purposes, and military industries. This plays an increasingly vital role in monitoring, military reconnaissance, and precision strikes. Achieving accurate and complete results through traditional methods is becoming more challenging because of the scattered complexity of polarization in polarimetric synthetic aperture radar (PolSAR) image. A multistage decision-based method is proposed composed of power decision, dominant scattering mechanism decision, and reflection symmetry decision. In addition, the theories of polarimetric contrast enhancement, generalized Y decomposition, and maximum eigenvalue ratio are applied to assist the decision. Fully PolSAR data are adopted to evaluate and verify the approach. Experimental results show that the method can achieve an effective result with a lower false alarm rate and clear contours. Finally, on this basis, a universal framework of change detection for manmade targets is presented as an application of our method. Two sets of measured data are also used to evaluate and verify the effectiveness of the change-detection algorithm.
Rodriguez-Florez, Naiara; Bruse, Jan L; Borghi, Alessandro; Vercruysse, Herman; Ong, Juling; James, Greg; Pennec, Xavier; Dunaway, David J; Jeelani, N U Owase; Schievano, Silvia
2017-10-01
Spring-assisted cranioplasty is performed to correct the long and narrow head shape of children with sagittal synostosis. Such corrective surgery involves osteotomies and the placement of spring-like distractors, which gradually expand to widen the skull until removal about 4 months later. Due to its dynamic nature, associations between surgical parameters and post-operative 3D head shape features are difficult to comprehend. The current study aimed at applying population-based statistical shape modelling to gain insight into how the choice of surgical parameters such as craniotomy size and spring positioning affects post-surgical head shape. Twenty consecutive patients with sagittal synostosis who underwent spring-assisted cranioplasty at Great Ormond Street Hospital for Children (London, UK) were prospectively recruited. Using a nonparametric statistical modelling technique based on mathematical currents, a 3D head shape template was computed from surface head scans of sagittal patients after spring removal. Partial least squares (PLS) regression was employed to quantify and visualise trends of localised head shape changes associated with the surgical parameters recorded during spring insertion: anterior-posterior and lateral craniotomy dimensions, anterior spring position and distance between anterior and posterior springs. Bivariate correlations between surgical parameters and corresponding PLS shape vectors demonstrated that anterior-posterior (Pearson's [Formula: see text]) and lateral craniotomy dimensions (Spearman's [Formula: see text]), as well as the position of the anterior spring ([Formula: see text]) and the distance between both springs ([Formula: see text]) on average had significant effects on head shapes at the time of spring removal. Such effects were visualised on 3D models. Population-based analysis of 3D post-operative medical images via computational statistical modelling tools allowed for detection of novel associations between surgical parameters and head shape features achieved following spring-assisted cranioplasty. The techniques described here could be extended to other cranio-maxillofacial procedures in order to assess post-operative outcomes and ultimately facilitate surgical decision making.
An intelligent multi-media human-computer dialogue system
NASA Technical Reports Server (NTRS)
Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.
1988-01-01
Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.
Development of a Common User Interface for the Launch Decision Support System
NASA Technical Reports Server (NTRS)
Scholtz, Jean C.
1991-01-01
The Launch Decision Support System (LDSS) is software to be used by the NASA Test Director (NTD) in the firing room during countdown. This software is designed to assist the NTD with time management, that is, when to resume from a hold condition. This software will assist the NTD in making and evaluating alternate plans and will keep him advised of the existing situation. As such, the interface to this software must be designed to provide the maximum amount of information in the clearest fashion and in a timely manner. This research involves applying user interface guidelines to a mature prototype of LDSS and developing displays that will enable the users to easily and efficiently obtain information from the LDSS displays. This research also extends previous work on organizing and prioritizing human-computer interaction knowledge.
Fast Image Texture Classification Using Decision Trees
NASA Technical Reports Server (NTRS)
Thompson, David R.
2011-01-01
Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.
ERIC Educational Resources Information Center
Lu, Hui-Chuan; Chu, Yu-Hsin; Chang, Cheng-Yu
2013-01-01
Compared with English learners, Spanish learners have fewer resources for automatic error detection and revision and following the current integrative Computer Assisted Language Learning (CALL), we combined corpus-based approach and CALL to create the System of Error Detection and Revision Suggestion (SEDRS) for learning Spanish. Through…
Computer-Assisted Detection of 90% of EFL Student Errors
ERIC Educational Resources Information Center
Harvey-Scholes, Calum
2018-01-01
Software can facilitate English as a Foreign Language (EFL) students' self-correction of their free-form writing by detecting errors; this article examines the proportion of errors which software can detect. A corpus of 13,644 words of written English was created, comprising 90 compositions written by Spanish-speaking students at levels A2-B2…
Eye Tracking and Head Movement Detection: A State-of-Art Survey
2013-01-01
Eye-gaze detection and tracking have been an active research field in the past years as it adds convenience to a variety of applications. It is considered a significant untraditional method of human computer interaction. Head movement detection has also received researchers' attention and interest as it has been found to be a simple and effective interaction method. Both technologies are considered the easiest alternative interface methods. They serve a wide range of severely disabled people who are left with minimal motor abilities. For both eye tracking and head movement detection, several different approaches have been proposed and used to implement different algorithms for these technologies. Despite the amount of research done on both technologies, researchers are still trying to find robust methods to use effectively in various applications. This paper presents a state-of-art survey for eye tracking and head movement detection methods proposed in the literature. Examples of different fields of applications for both technologies, such as human-computer interaction, driving assistance systems, and assistive technologies are also investigated. PMID:27170851
Predictive analytics and child protection: constraints and opportunities.
Russell, Jesse
2015-08-01
This paper considers how predictive analytics might inform, assist, and improve decision making in child protection. Predictive analytics represents recent increases in data quantity and data diversity, along with advances in computing technology. While the use of data and statistical modeling is not new to child protection decision making, its use in child protection is experiencing growth, and efforts to leverage predictive analytics for better decision-making in child protection are increasing. Past experiences, constraints and opportunities are reviewed. For predictive analytics to make the most impact on child protection practice and outcomes, it must embrace established criteria of validity, equity, reliability, and usefulness. Copyright © 2015 Elsevier Ltd. All rights reserved.
Locally adaptive decision in detection of clustered microcalcifications in mammograms.
Sainz de Cea, María V; Nishikawa, Robert M; Yang, Yongyi
2018-02-15
In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value <10 -4 ). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.
Locally adaptive decision in detection of clustered microcalcifications in mammograms
NASA Astrophysics Data System (ADS)
Sainz de Cea, María V.; Nishikawa, Robert M.; Yang, Yongyi
2018-02-01
In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value <10-4). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.
Vasconcelos, Francisco; Brandão, Patrick; Vercauteren, Tom; Ourselin, Sebastien; Deprest, Jan; Peebles, Donald; Stoyanov, Danail
2018-06-27
Intrauterine foetal surgery is the treatment option for several congenital malformations. For twin-to-twin transfusion syndrome (TTTS), interventions involve the use of laser fibre to ablate vessels in a shared placenta. The procedure presents a number of challenges for the surgeon, and computer-assisted technologies can potentially be a significant support. Vision-based sensing is the primary source of information from the intrauterine environment, and hence, vision approaches present an appealing approach for extracting higher level information from the surgical site. In this paper, we propose a framework to detect one of the key steps during TTTS interventions-ablation. We adopt a deep learning approach, specifically the ResNet101 architecture, for classification of different surgical actions performed during laser ablation therapy. We perform a two-fold cross-validation using almost 50 k frames from five different TTTS ablation procedures. Our results show that deep learning methods are a promising approach for ablation detection. To our knowledge, this is the first attempt at automating photocoagulation detection using video and our technique can be an important component of a larger assistive framework for enhanced foetal therapies. The current implementation does not include semantic segmentation or localisation of the ablation site, and this would be a natural extension in future work.
NASA Astrophysics Data System (ADS)
Rimland, Jeffrey; McNeese, Michael; Hall, David
2013-05-01
Although the capability of computer-based artificial intelligence techniques for decision-making and situational awareness has seen notable improvement over the last several decades, the current state-of-the-art still falls short of creating computer systems capable of autonomously making complex decisions and judgments in many domains where data is nuanced and accountability is high. However, there is a great deal of potential for hybrid systems in which software applications augment human capabilities by focusing the analyst's attention to relevant information elements based on both a priori knowledge of the analyst's goals and the processing/correlation of a series of data streams too numerous and heterogeneous for the analyst to digest without assistance. Researchers at Penn State University are exploring ways in which an information framework influenced by Klein's (Recognition Primed Decision) RPD model, Endsley's model of situational awareness, and the Joint Directors of Laboratories (JDL) data fusion process model can be implemented through a novel combination of Complex Event Processing (CEP) and Multi-Agent Software (MAS). Though originally designed for stock market and financial applications, the high performance data-driven nature of CEP techniques provide a natural compliment to the proven capabilities of MAS systems for modeling naturalistic decision-making, performing process adjudication, and optimizing networked processing and cognition via the use of "mobile agents." This paper addresses the challenges and opportunities of such a framework for augmenting human observational capability as well as enabling the ability to perform collaborative context-aware reasoning in both human teams and hybrid human / software agent teams.
The Assisted Decision-Making (Capacity) Bill 2013: content, commentary, controversy.
Kelly, B D
2015-03-01
Ireland's Assisted Decision-Making (Capacity) Bill (2013) aims to reform the law relating to persons who require assistance exercising their decision-making capacity. When finalised, the Bill will replace Ireland's outdated Ward of Court system which has an all-or-nothing approach to capacity; does not adequately define capacity; is poorly responsive to change; makes unwieldy provision for appointing decision-makers; and has insufficient provision for review. To explore the content and implications of the Assisted Decision-Making (Capacity) Bill. Review of the content of the Assisted Decision-Making (Capacity) Bill and related literature. The new Bill includes a presumption of capacity and defines lack of capacity. All interventions must minimise restriction of rights and freedom, and have due regard for "dignity, bodily integrity, privacy and autonomy". The Bill proposes legal frameworks for "assisted decision-making" (where an individual voluntarily appoints someone to assist with specific decisions relating to personal welfare or property and affairs, by, among other measures, assisting the individual to communicate his or her "will and preferences"); "co-decision-making" (where the Circuit Court declares the individual's capacity is reduced but he or she can make specific decisions with a co-decision-maker to share authority); "decision-making representatives" (substitute decision-making); "enduring power of attorney"; and "informal decision-making on personal welfare matters" (without apparent oversight). These measures, if implemented, will shift Ireland's capacity laws away from an approach based on "best interests" to one based on "will and preferences", and increase compliance with the United Nations' Convention on the Rights of Persons with Disabilities.
Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries
Davuluri, Pavani; Wu, Jie; Tang, Yang; Cockrell, Charles H.; Ward, Kevin R.; Najarian, Kayvan; Hargraves, Rosalyn H.
2012-01-01
Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising. PMID:22919433
Expert System Detects Power-Distribution Faults
NASA Technical Reports Server (NTRS)
Walters, Jerry L.; Quinn, Todd M.
1994-01-01
Autonomous Power Expert (APEX) computer program is prototype expert-system program detecting faults in electrical-power-distribution system. Assists human operators in diagnosing faults and deciding what adjustments or repairs needed for immediate recovery from faults or for maintenance to correct initially nonthreatening conditions that could develop into faults. Written in Lisp.
Likelihood ratio decisions in memory: three implied regularities.
Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T
2009-06-01
We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.
ERIC Educational Resources Information Center
Judd, Wilson A.
A study was conducted to investigate learner control of instruction in contrast to response sensitive branching algorithms with respect to two specific types of instructional decisions: (1) whether a student should enter and study a particular instructional module given his score on an associated diagnostic pretest; and (2) when a student should…
Adaptive Computer-Assisted Mammography Training for Improved Breast Cancer Screening
2013-10-01
diagnostic decision, and image content." Journal of the American Medical Informatics Association. Voisin, S., F. Pinto, G. Morin-Ducote, K. B. Hudson and G...fatigue at the end of a long work day may skip a step in his or her search pattern and forget to look at a portion of the breast. While attempts are made
Dodd, Lori E; Wagner, Robert F; Armato, Samuel G; McNitt-Gray, Michael F; Beiden, Sergey; Chan, Heang-Ping; Gur, David; McLennan, Geoffrey; Metz, Charles E; Petrick, Nicholas; Sahiner, Berkman; Sayre, Jim
2004-04-01
Cancer of the lung and bronchus is the leading fatal malignancy in the United States. Five-year survival is low, but treatment of early stage disease considerably improves chances of survival. Advances in multidetector-row computed tomography technology provide detection of smaller lung nodules and offer a potentially effective screening tool. The large number of images per exam, however, requires considerable radiologist time for interpretation and is an impediment to clinical throughput. Thus, computer-aided diagnosis (CAD) methods are needed to assist radiologists with their decision making. To promote the development of CAD methods, the National Cancer Institute formed the Lung Image Database Consortium (LIDC). The LIDC is charged with developing the consensus and standards necessary to create an image database of multidetector-row computed tomography lung images as a resource for CAD researchers. To develop such a prospective database, its potential uses must be anticipated. The ultimate applications will influence the information that must be included along with the images, the relevant measures of algorithm performance, and the number of required images. In this article we outline assessment methodologies and statistical issues as they relate to several potential uses of the LIDC database. We review methods for performance assessment and discuss issues of defining "truth" as well as the complications that arise when truth information is not available. We also discuss issues about sizing and populating a database.
Editorial Comments, 1974-1986: The Case For and Against the Use of Computer-Assisted Decision Making
Weaver, Robert R.
1987-01-01
Journal editorials are an important medium for communicating information about medical innovations. Evaluative statements contained in editorials pertain to the innovation's technical merits, as well as its probable economic, social and political, and ethical consequences. This information will either promote or impede the subsequent diffusion of innovations. This paper analyzes the evaluative information contained in thirty editorials that pertain to the topic of computer-assisted decision making (CDM). Most editorials agree that CDM technology is effective and economical in performing routine clinical tasks; controversy surrounds the use of more sophisticated CDM systems for complex problem solving. A few editorials argue that the innovation should play an integral role in transforming the established health care system. Most, however, maintain that it can or should be accommodated within the existing health care framework. Finally, while few editorials discuss the ethical ramifications of CDM technology, those that do suggest that it will contribute to more humane health care. The editorial analysis suggests that CDM technology aimed at routine clinical task will experience rapid diffusion. In contrast, the diffusion of more sophisticated CDM systems will, in the foreseeable future, likely be sporadic at best.
Impact of model-based risk analysis for liver surgery planning.
Hansen, C; Zidowitz, S; Preim, B; Stavrou, G; Oldhafer, K J; Hahn, H K
2014-05-01
A model-based risk analysis for oncologic liver surgery was described in previous work (Preim et al. in Proceedings of international symposium on computer assisted radiology and surgery (CARS), Elsevier, Amsterdam, pp. 353–358, 2002; Hansen et al. Int I Comput Assist Radiol Surg 4(5):469–474, 2009). In this paper, we present an evaluation of this method. To prove whether and how the risk analysis facilitates the process of liver surgery planning, an explorative user study with 10 liver experts was conducted. The purpose was to compare and analyze their decision-making. The results of the study show that model-based risk analysis enhances the awareness of surgical risk in the planning stage. Participants preferred smaller resection volumes and agreed more on the safety margins’ width in case the risk analysis was available. In addition, time to complete the planning task and confidence of participants were not increased when using the risk analysis. This work shows that the applied model-based risk analysis may influence important planning decisions in liver surgery. It lays a basis for further clinical evaluations and points out important fields for future research.
NASA Technical Reports Server (NTRS)
Buechler, W.; Tucker, A. G.
1981-01-01
Several methods were employed to detect both the occurrence and source of errors in the operational software of the AN/SLQ-32. A large embedded real time electronic warfare command and control system for the ROLM 1606 computer are presented. The ROLM computer provides information about invalid addressing, improper use of privileged instructions, stack overflows, and unimplemented instructions. Additionally, software techniques were developed to detect invalid jumps, indices out of range, infinte loops, stack underflows, and field size errors. Finally, data are saved to provide information about the status of the system when an error is detected. This information includes I/O buffers, interrupt counts, stack contents, and recently passed locations. The various errors detected, techniques to assist in debugging problems, and segment simulation on a nontarget computer are discussed. These error detection techniques were a major factor in the success of finding the primary cause of error in 98% of over 500 system dumps.
Anandasabapathy, Sharmila; Sontag, Stephen; Graham, David Y; Frist, Stephen; Bratton, Joan; Harpaz, Noam; Waye, Jerome D
2011-03-01
Barrett's epithelial dysplasia, the direct precursor to esophageal adenocarcinoma, is often unapparent and frequently missed during surveillance of Barrett's esophagus with four-quadrant forceps biopsy protocol. To determine whether the detection of dysplasia is improved by adding computer-assisted brush biopsy (EndoCDx©) to four-quadrant biopsy protocol. Patients with a history of Barrett's esophagus with dysplasia scheduled for endoscopic surveillance were recruited from four academic medical centers. Patients underwent brush biopsy followed by four-quadrant biopsy every 1-2 cm. The results from brush and forceps biopsy were reviewed independently by pathologists blinded to the other's results. Among 151 patients enrolled (124 men, 27 women; mean age: 65), 117 (77.5%) had forceps and brush-biopsy specimens adequate for interpretation. The mean number of forceps biopsies was 11.9 (median 10, range 2-40) and brush biopsies was 2.0 (median 2, range 1-4). The overall yield of forceps alone was 25.2% (n = 38). Brush biopsy added an additional 16 positive cases increasing the yield of dysplasia detection by 42% (95% CI: 20.7-72.7). The number needed to test (NNT) to detect one additional case of dysplasia was 9.4 (95% CI: 6.4-17.7). There were no significant differences in results among different centers, between standard versus jumbo forceps, or between forceps biopsies taken every 1 cm versus every 2 cm. These data suggest that computer-assisted brush biopsy is a useful adjunct to standard endoscopic surveillance regimens for the identification of dysplasia in Barrett's esophagus.
A Vision-Based System for Object Identification and Information Retrieval in a Smart Home
NASA Astrophysics Data System (ADS)
Grech, Raphael; Monekosso, Dorothy; de Jager, Deon; Remagnino, Paolo
This paper describes a hand held device developed to assist people to locate and retrieve information about objects in a home. The system developed is a standalone device to assist persons with memory impairments such as people suffering from Alzheimer's disease. A second application is object detection and localization for a mobile robot operating in an ambient assisted living environment. The device relies on computer vision techniques to locate a tagged object situated in the environment. The tag is a 2D color printed pattern with a detection range and a field of view such that the user may point from a distance of over 1 meter.
An approach to quality and performance control in a computer-assisted clinical chemistry laboratory.
Undrill, P E; Frazer, S C
1979-01-01
A locally developed, computer-based clinical chemistry laboratory system has been in operation since 1970. This utilises a Digital Equipment Co Ltd PDP 12 and an interconnected PDP 8/F computer. Details are presented of the performance and quality control techniques incorporated into the system. Laboratory performance is assessed through analysis of results from fixed-level control sera as well as from cumulative sum methods. At a simple level the presentation may be considered purely indicative, while at a more sophisticated level statistical concepts have been introduced to aid the laboratory controller in decision-making processes. PMID:438340
AdaBoost-based algorithm for network intrusion detection.
Hu, Weiming; Hu, Wei; Maybank, Steve
2008-04-01
Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.
NASA Technical Reports Server (NTRS)
Simpson, Robert W.
1993-01-01
This presentation outlines a concept for an adaptive, interactive decision support system to assist controllers at a busy airport in achieving efficient use of multiple runways. The concept is being implemented as a computer code called FASA (Final Approach Spacing for Aircraft), and will be tested and demonstrated in ATCSIM, a high fidelity simulation of terminal area airspace and airport surface operations. Objectives are: (1) to provide automated cues to assist controllers in the sequencing and spacing of landing and takeoff aircraft; (2) to provide the controller with a limited ability to modify the sequence and spacings between aircraft, and to insert takeoffs and missed approach aircraft in the landing flows; (3) to increase spacing accuracy using more complex and precise separation criteria while reducing controller workload; and (4) achieve higher operational takeoff and landing rates on multiple runways in poor visibility.
Hoard, Christopher J.; Fogarty, Lisa R.; Duris, Joseph W.
2018-02-21
In 1998, the Michigan Department of Environmental Quality and the U.S. Geological Survey began the Water Chemistry Monitoring Program for select streams in the State of Michigan. Objectives of this program were to provide assistance with (1) statewide water-quality assessments, (2) the National Pollutant Discharge Elimination System permitting process, and (3) water-resource management decisions. As part of this program, water-quality data collected from 1998 to 2013 were analyzed to identify potential trends for select constituents that were sampled. Sixteen water-quality constituents were analyzed at 32 stations throughout Michigan. Trend analysis on the various water-quality data was done using either the uncensored Seasonal Kendall test or through Tobit regression. In total, 79 trends were detected in the constituents analyzed for 32 river stations sampled for the study period—53 downward trends and 26 upward trends were detected. The most prevalent trend detected throughout the State was for ammonia, with 11 downward trends and 1 upward trend estimated.In addition to trends, constituent loads were estimated for 31 stations from 2002 to 2013 for stations that were sampled 12 times per year. Loads were computed using the Autobeale load computation program, which used the Beale ratio estimator approach to estimate an annual load. Constituent loads were the largest in large watershed streams with the highest annual flows such as the Saginaw and Grand Rivers. Likewise, constituent loads were the smallest in smaller tributaries that were sampled as part of this program such as the Boardman and Thunder Bay Rivers.
Renewal of the Attentive Sensing Project
2006-02-07
decisions about target presence or absence, is denoted track before detect . We have investigated joint tracking and detection in the context of the foveal...computationally tractable bounds. 4 Task 2: Sensor Configuration for Tracking and Track Before Detect Task 2 consisted of investigation of attentive...strategy to multiple targets and to track before detect sensors. To apply principles developed in the context of foveal sensors to more immediately
Computational Support for Technology- Investment Decisions
NASA Technical Reports Server (NTRS)
Adumitroaie, Virgil; Hua, Hook; Lincoln, William; Block, Gary; Mrozinski, Joseph; Shelton, Kacie; Weisbin, Charles; Elfes, Alberto; Smith, Jeffrey
2007-01-01
Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
This technical note describes the current capabilities and availability of the Automated Dredging and Disposal Alternatives Management System (ADDAMS). The technical note replaces the earlier Technical Note EEDP-06-12, which should be discarded. Planning, design, and management of dredging and dredged material disposal projects often require complex or tedious calculations or involve complex decision-making criteria. In addition, the evaluations often must be done for several disposal alternatives or disposal sites. ADDAMS is a personal computer (PC)-based system developed to assist in making such evaluations in a timely manner. ADDAMS contains a collection of computer programs (applications) designed to assist in managingmore » dredging projects. This technical note describes the system, currently available applications, mechanisms for acquiring and running the system, and provisions for revision and expansion.« less
NASA Astrophysics Data System (ADS)
Kollat, J. B.; Reed, P. M.
2009-12-01
This study contributes the ASSIST (Adaptive Strategies for Sampling in Space and Time) framework for improving long-term groundwater monitoring decisions across space and time while accounting for the influences of systematic model errors (or predictive bias). The ASSIST framework combines contaminant flow-and-transport modeling, bias-aware ensemble Kalman filtering (EnKF) and many-objective evolutionary optimization. Our goal in this work is to provide decision makers with a fuller understanding of the information tradeoffs they must confront when performing long-term groundwater monitoring network design. Our many-objective analysis considers up to 6 design objectives simultaneously and consequently synthesizes prior monitoring network design methodologies into a single, flexible framework. This study demonstrates the ASSIST framework using a tracer study conducted within a physical aquifer transport experimental tank located at the University of Vermont. The tank tracer experiment was extensively sampled to provide high resolution estimates of tracer plume behavior. The simulation component of the ASSIST framework consists of stochastic ensemble flow-and-transport predictions using ParFlow coupled with the Lagrangian SLIM transport model. The ParFlow and SLIM ensemble predictions are conditioned with tracer observations using a bias-aware EnKF. The EnKF allows decision makers to enhance plume transport predictions in space and time in the presence of uncertain and biased model predictions by conditioning them on uncertain measurement data. In this initial demonstration, the position and frequency of sampling were optimized to: (i) minimize monitoring cost, (ii) maximize information provided to the EnKF, (iii) minimize failure to detect the tracer, (iv) maximize the detection of tracer flux, (v) minimize error in quantifying tracer mass, and (vi) minimize error in quantifying the moment of the tracer plume. The results demonstrate that the many-objective problem formulation provides a tremendous amount of information for decision makers. Specifically our many-objective analysis highlights the limitations and potentially negative design consequences of traditional single and two-objective problem formulations. These consequences become apparent through visual exploration of high-dimensional tradeoffs and the identification of regions with interesting compromise solutions. The prediction characteristics of these compromise designs are explored in detail, as well as their implications for subsequent design decisions in both space and time.
Computer aided detection system for lung cancer using computer tomography scans
NASA Astrophysics Data System (ADS)
Mahesh, Shanthi; Rakesh, Spoorthi; Patil, Vidya C.
2018-04-01
Lung Cancer is a disease can be defined as uncontrolled cell growth in tissues of the lung. If we detect the Lung Cancer in its early stage, then that could be the key of its cure. In this work the non-invasive methods are studied for assisting in nodule detection. It supplies a Computer Aided Diagnosis System (CAD) for early detection of lung cancer nodules from the Computer Tomography (CT) images. CAD system is the one which helps to improve the diagnostic performance of radiologists in their image interpretations. The main aim of this technique is to develop a CAD system for finding the lung cancer using the lung CT images and classify the nodule as Benign or Malignant. For classifying cancer cells, SVM classifier is used. Here, image processing techniques have been used to de-noise, to enhance, for segmentation and edge detection of an image is used to extract the area, perimeter and shape of nodule. The core factors of this research are Image quality and accuracy.
USDA-ARS?s Scientific Manuscript database
Resazurin dye is an effective way to test the metabolism of sperm. As sperm move, they create metabolic waste which is detected by the dye. Another way sperm are evaluated is by Computer-Assisted Sperm Analysis (CASA). CASA detects motility, progression, curvilinear velocity, lateral head amplitude,...
NASA Astrophysics Data System (ADS)
Traverso, A.; Lopez Torres, E.; Fantacci, M. E.; Cerello, P.
2017-05-01
Lung cancer is one of the most lethal types of cancer, because its early diagnosis is not good enough. In fact, the detection of pulmonary nodule, potential lung cancers, in Computed Tomography scans is a very challenging and time-consuming task for radiologists. To support radiologists, researchers have developed Computer-Aided Diagnosis (CAD) systems for the automated detection of pulmonary nodules in chest Computed Tomography scans. Despite the high level of technological developments and the proved benefits on the overall detection performance, the usage of Computer-Aided Diagnosis in clinical practice is far from being a common procedure. In this paper we investigate the causes underlying this discrepancy and present a solution to tackle it: the M5L WEB- and Cloud-based on-demand Computer-Aided Diagnosis. In addition, we prove how the combination of traditional imaging processing techniques with state-of-art advanced classification algorithms allows to build a system whose performance could be much larger than any Computer-Aided Diagnosis developed so far. This outcome opens the possibility to use the CAD as clinical decision support for radiologists.
Retinal imaging analysis based on vessel detection.
Jamal, Arshad; Hazim Alkawaz, Mohammed; Rehman, Amjad; Saba, Tanzila
2017-07-01
With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art. © 2017 Wiley Periodicals, Inc.
Giger, Maryellen L.; Chan, Heang-Ping; Boone, John
2008-01-01
The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists’ goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities that are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists—as opposed to a completely automatic computer interpretation—focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous—from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects—collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more—from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis. PMID:19175137
DOE Office of Scientific and Technical Information (OSTI.GOV)
Giger, Maryellen L.; Chan, Heang-Ping; Boone, John
2008-12-15
The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists' goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities thatmore » are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists--as opposed to a completely automatic computer interpretation--focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous--from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects--collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more--from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis.« less
NASA Astrophysics Data System (ADS)
Barros, George O.; Navarro, Brenda; Duarte, Angelo; Dos-Santos, Washington L. C.
2017-04-01
PathoSpotter is a computational system designed to assist pathologists in teaching about and researching kidney diseases. PathoSpotter-K is the version that was developed to detect nephrological lesions in digital images of kidneys. Here, we present the results obtained using the first version of PathoSpotter-K, which uses classical image processing and pattern recognition methods to detect proliferative glomerular lesions with an accuracy of 88.3 ± 3.6%. Such performance is only achieved by similar systems if they use images of cell in contexts that are much less complex than the glomerular structure. The results indicate that the approach can be applied to the development of systems designed to train pathology students and to assist pathologists in determining large-scale clinicopathological correlations in morphological research.
[Cost analysis for navigation in knee endoprosthetics].
Cerha, O; Kirschner, S; Günther, K-P; Lützner, J
2009-12-01
Total knee arthroplasty (TKA) is one of the most frequent procedures in orthopaedic surgery. The outcome depends on a range of factors including alignment of the leg and the positioning of the implant in addition to patient-associated factors. Computer-assisted navigation systems can improve the restoration of a neutral leg alignment. This procedure has been established especially in Europe and North America. The additional expenses are not reimbursed in the German DRG system (Diagnosis Related Groups). In the present study a cost analysis of computer-assisted TKA compared to the conventional technique was performed. The acquisition expenses of various navigation systems (5 and 10 year depreciation), annual costs for maintenance and software updates as well as the accompanying costs per operation (consumables, additional operating time) were considered. The additional operating time was determined on the basis of a meta-analysis according to the current literature. Situations with 25, 50, 100, 200 and 500 computer-assisted TKAs per year were simulated. The amount of the incremental costs of the computer-assisted TKA depends mainly on the annual volume and the additional operating time. A relevant decrease of the incremental costs was detected between 50 and 100 procedures per year. In a model with 100 computer-assisted TKAs per year an additional operating time of 14 mins and a 10 year depreciation of the investment costs, the incremental expenses amount to
Gunay, Osman; Toreyin, Behçet Ugur; Kose, Kivanc; Cetin, A Enis
2012-05-01
In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.
Digital video applications in radiologic education: theory, technique, and applications.
Hennessey, J G; Fishman, E K; Ney, D R
1994-05-01
Computer-assisted instruction (CAI) has great potential in medical education. The recent explosion of multimedia platforms provides an environment for the seemless integration of text, images, and sound into a single program. This article discusses the role of digital video in the current educational environment as well as its future potential. An indepth review of the technical decisions of this new technology is also presented.
DoD Research and Engineering Enterprise
2014-05-01
Secretary of Defense Hagel, Pentagon Press Briefing Room, February 24, 2014 Technological superiority has been central to the strategy of the...understand the environment, to software algorithms that can make a decision or seek human assistance. Through autonomy, we should be able to greatly reduce...computers are a commercial product 1 , and quantum key distribution for data encryption is nearly a commercial product. These two applications are
ERIC Educational Resources Information Center
Marble, James E.; And Others
The community colleges in the state of Washington are committed to a Six Year Plan to provide computing and information systems support to all students. The system is intended to make available a broad range of career placement information to assist decision-making, thereby humanizing education by insuring fewer misguided students, counselors and…
ERIC Educational Resources Information Center
Wollmer, Richard D.; Bond, Nicholas A.
Two computer-assisted instruction programs were written in electronics and trigonometry to test the Wollmer Markov Model for optimizing hierarchial learning; calibration samples totalling 110 students completed these programs. Since the model postulated that transfer effects would be a function of the amount of practice, half of the students were…
Alkasab, Tarik K; Bizzo, Bernardo C; Berland, Lincoln L; Nair, Sujith; Pandharipande, Pari V; Harvey, H Benjamin
2017-09-01
Decreasing unnecessary variation in radiology reporting and producing guideline-concordant reports is fundamental to radiology's success in value-based payment models and good for patient care. In this article, we present an open authoring system for point-of-care clinical decision support tools integrated into the radiologist reporting environment referred to as the computer-assisted reporting and decision support (CAR/DS) framework. The CAR/DS authoring system, described herein, includes: (1) a definition format for representing radiology clinical guidelines as structured, machine-readable Extensible Markup Language documents and (2) a user-friendly reference implementation to test the fidelity of the created definition files with the clinical guideline. The proposed definition format and reference implementation will enable content creators to develop CAR/DS tools that voice recognition software (VRS) vendors can use to extend the commercial tools currently in use. In making the definition format and reference implementation software freely available, we hope to empower individual radiologists, expert groups such as the ACR, and VRS vendors to develop a robust ecosystem of CAR/DS tools that can further improve the quality and efficiency of the patient care that our field provides. We hope that this initial effort can serve as the basis for a community-owned open standard for guideline definition that the imaging informatics and VRS vendor communities will embrace and strengthen. To this end, the ACR Assist™ initiative is intended to make the College's clinical content, including the Incidental Findings Committee White Papers, available for decision support tool creation based upon the herein described CAR/DS framework. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.
The influence of performance on action-effect integration in sense of agency.
Wen, Wen; Yamashita, Atsushi; Asama, Hajime
2017-08-01
Sense of agency refers to the subjective feeling of being able to control an outcome through one's own actions or will. Prior studies have shown that both sensory processing (e.g., comparisons between sensory feedbacks and predictions basing on one's motor intentions) and high-level cognitive/constructive processes (e.g., inferences based on one's performance or the consequences of one's actions) contribute to judgments of sense of agency. However, it remains unclear how these two types of processes interact, which is important for clarifying the mechanisms underlying sense of agency. Thus, we examined whether performance-based inferences influence action-effect integration in sense of agency using a delay detection paradigm in two experiments. In both experiments, participants pressed left and right arrow keys to control the direction in which a moving dot was travelling. The dot's response delay was manipulated randomly on 7 levels (0-480ms) between the trials; for each trial, participants were asked to judge whether the dot response was delayed and to rate their level of agency over the dot. In Experiment 1, participants tried to direct the dot to reach a destination on the screen as quickly as possible. Furthermore, the computer assisted participants by ignoring erroneous commands for half of the trials (assisted condition), while in the other half, all of the participants' commands were executed (self-control condition). In Experiment 2, participants directed the dot as they pleased (without a specific goal), but, in half of the trials, the computer randomly ignored 32% of their commands (disturbed condition) rather than assisted them. The results from the two experiments showed that performance enhanced action-effect integration. Specifically, when task performance was improved through the computer's assistance in Experiment 1, delay detection was reduced in the 480-ms delay condition, despite the fact that 32% of participants' commands were ignored. Conversely, when no feedback on task performance was given (as in Experiment 2), the participants reported greater delay when some of their commands were randomly ignored. Furthermore, the results of a logistic regression analysis showed that the threshold of delay detection was greater in the assisted condition than in the self-control condition in Experiment 1, which suggests a wider time window for action-effect integration. A multivariate analysis also revealed that assistance was related to reduced delay detection via task performance, while reduced delay detection was directly correlated with a better sense of agency. These results indicate an association between the implicit and explicit aspects of sense of agency. Copyright © 2017 Elsevier Inc. All rights reserved.
Monitoring and decision making by people in man machine systems
NASA Technical Reports Server (NTRS)
Johannsen, G.
1979-01-01
The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.
NASA Astrophysics Data System (ADS)
Chaisaowong, Kraisorn; Jiang, Mingze; Faltin, Peter; Merhof, Dorit; Eisenhawer, Christian; Gube, Monika; Kraus, Thomas
2016-03-01
Pleural thickenings are caused by asbestos exposure and may evolve into malignant pleural mesothelioma. An early diagnosis plays a key role towards an early treatment and an increased survival rate. Today, pleural thickenings are detected by visual inspection of CT data, which is time-consuming and underlies the physician's subjective judgment. A computer-assisted diagnosis system to automatically assess pleural thickenings has been developed, which includes not only a quantitative assessment with respect to size and location, but also enhances this information with an anatomical description, i.e. lung side (left, right), part of pleura (pars costalis, mediastinalis, diaphragmatica, spinalis), as well as vertical (upper, middle, lower) and horizontal (ventral, dorsal) position. For this purpose, a 3D anatomical model of the lung surface has been manually constructed as a 3D atlas. Three registration sub-steps including rigid, affine, and nonrigid registration align the input patient lung to the 3D anatomical atlas model of the lung surface. Finally, each detected pleural thickening is assigned a set of labels describing its anatomical properties. Through this added information, an enhancement to the existing computer-assisted diagnosis system is presented in order to assure a higher precision and reproducible assessment of pleural thickenings, aiming at the diagnosis of the pleural mesothelioma in its early stage.
Clarification process: Resolution of decision-problem conditions
NASA Technical Reports Server (NTRS)
Dieterly, D. L.
1980-01-01
A model of a general process which occurs in both decisionmaking and problem-solving tasks is presented. It is called the clarification model and is highly dependent on information flow. The model addresses the possible constraints of individual indifferences and experience in achieving success in resolving decision-problem conditions. As indicated, the application of the clarification process model is only necessary for certain classes of the basic decision-problem condition. With less complex decision problem conditions, certain phases of the model may be omitted. The model may be applied across a wide range of decision problem conditions. The model consists of two major components: (1) the five-phase prescriptive sequence (based on previous approaches to both concepts) and (2) the information manipulation function (which draws upon current ideas in the areas of information processing, computer programming, memory, and thinking). The two components are linked together to provide a structure that assists in understanding the process of resolving problems and making decisions.
A Fast Approach to Automatic Detection of Brain Lesions
Koley, Subhranil; Chakraborty, Chandan; Mainero, Caterina; Fischl, Bruce; Aganj, Iman
2017-01-01
Template matching is a popular approach to computer-aided detection of brain lesions from magnetic resonance (MR) images. The outcomes are often sufficient for localizing lesions and assisting clinicians in diagnosis. However, processing large MR volumes with three-dimensional (3D) templates is demanding in terms of computational resources, hence the importance of the reduction of computational complexity of template matching, particularly in situations in which time is crucial (e.g. emergent stroke). In view of this, we make use of 3D Gaussian templates with varying radii and propose a new method to compute the normalized cross-correlation coefficient as a similarity metric between the MR volume and the template to detect brain lesions. Contrary to the conventional fast Fourier transform (FFT) based approach, whose runtime grows as O(N logN) with the number of voxels, the proposed method computes the cross-correlation in O(N). We show through our experiments that the proposed method outperforms the FFT approach in terms of computational time, and retains comparable accuracy. PMID:29082383
NASA Astrophysics Data System (ADS)
Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv
2018-02-01
New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.
Tool for Ranking Research Options
NASA Technical Reports Server (NTRS)
Ortiz, James N.; Scott, Kelly; Smith, Harold
2005-01-01
Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.
Filippini, D; Tejle, K; Lundström, I
2005-08-15
The computer screen photo-assisted technique (CSPT), a method for substance classification based on spectral fingerprinting, which involves just a computer screen and a web camera as measuring platform is used here for the evaluation of a prospective enzyme-linked immunosorbent assay (ELISA). A anti-neutrophil cytoplasm antibodies (ANCA-ELISA) test, typically used for diagnosing patients suffering from chronic inflammatory disorders in the skin, joints, blood vessels and other tissues is comparatively tested with a standard microplate reader and CSPT, yielding equivalent results at a fraction of the instrumental costs. The CSPT approach is discussed as a distributed measuring platform allowing decentralized measurements in routine applications, whereas keeping centralized information management due to its natural network embedded operation.
Assisting the visually impaired: obstacle detection and warning system by acoustic feedback.
Rodríguez, Alberto; Yebes, J Javier; Alcantarilla, Pablo F; Bergasa, Luis M; Almazán, Javier; Cela, Andrés
2012-12-17
The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system.
Assisting the Visually Impaired: Obstacle Detection and Warning System by Acoustic Feedback
Rodríguez, Alberto; Yebes, J. Javier; Alcantarilla, Pablo F.; Bergasa, Luis M.; Almazán, Javier; Cela, Andrés
2012-01-01
The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system. PMID:23247413
A novel mechatronic tool for computer-assisted arthroscopy.
Dario, P; Carrozza, M C; Marcacci, M; D'Attanasio, S; Magnami, B; Tonet, O; Megali, G
2000-03-01
This paper describes a novel mechatronic tool for arthroscopy, which is at the same time a smart tool for traditional arthroscopy and the main component of a system for computer-assisted arthroscopy. The mechatronic arthroscope has a cable-actuated servomotor-driven multi-joint mechanical structure, is equipped with a position sensor measuring the orientation of the tip and with a force sensor detecting possible contact with delicate tissues in the knee, and incorporates an embedded microcontroller for sensor signal processing, motor driving and interfacing with the surgeon and/or the system control unit. When used manually, the mechatronic arthroscope enhances the surgeon's capabilities by enabling him/her to easily control tip motion and to prevent undesired contacts. When the tool is integrated in a complete system for computer-assisted arthroscopy, the trajectory of the arthroscope is reconstructed in real time by an optical tracking system using infrared emitters located in the handle, providing advantages in terms of improved intervention accuracy. The computer-assisted arthroscopy system comprises an image processing module for segmentation and three-dimensional reconstruction of preoperative computer tomography or magnetic resonance images, a registration module for measuring the position of the knee joint, tracking the trajectory of the operating tools, and matching preoperative and intra-operative images, and a human-machine interface that displays the enhanced reality scenario and data from the mechatronic arthroscope in a friendly and intuitive manner. By integrating preoperative and intra-operative images and information provided by the mechatronic arthroscope, the system allows virtual navigation in the knee joint during the planning phase and computer guidance by augmented reality during the intervention. This paper describes in detail the characteristics of the mechatronic arthroscope and of the system for computer-assisted arthroscopy and discusses experimental results obtained with a preliminary version of the tool and of the system.
Artificial neural networks in mammography interpretation and diagnostic decision making.
Ayer, Turgay; Chen, Qiushi; Burnside, Elizabeth S
2013-01-01
Screening mammography is the most effective means for early detection of breast cancer. Although general rules for discriminating malignant and benign lesions exist, radiologists are unable to perfectly detect and classify all lesions as malignant and benign, for many reasons which include, but are not limited to, overlap of features that distinguish malignancy, difficulty in estimating disease risk, and variability in recommended management. When predictive variables are numerous and interact, ad hoc decision making strategies based on experience and memory may lead to systematic errors and variability in practice. The integration of computer models to help radiologists increase the accuracy of mammography examinations in diagnostic decision making has gained increasing attention in the last two decades. In this study, we provide an overview of one of the most commonly used models, artificial neural networks (ANNs), in mammography interpretation and diagnostic decision making and discuss important features in mammography interpretation. We conclude by discussing several common limitations of existing research on ANN-based detection and diagnostic models and provide possible future research directions.
77 FR 10744 - Agency Information Collection Activities; Submission for OMB Review; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-23
... establish disclosure requirements that assist consumers in making informed purchasing decisions, and... establish disclosure requirements that assist consumers in making informed purchasing decisions and... disclosure requirements that assist consumers in making informed purchasing decisions, and recordkeeping...
76 FR 77230 - Agency Information Collection Activities; Proposed Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-12
... consumers in making informed purchasing decisions, and recordkeeping requirements that assist the Commission... Rules establish disclosure requirements that assist consumers in making informed purchasing decisions... consumers in making informed purchasing decisions, and recordkeeping requirements that assist the Commission...
Image Analysis via Soft Computing: Prototype Applications at NASA KSC and Product Commercialization
NASA Technical Reports Server (NTRS)
Dominguez, Jesus A.; Klinko, Steve
2011-01-01
This slide presentation reviews the use of "soft computing" which differs from "hard computing" in that it is more tolerant of imprecision, partial truth, uncertainty, and approximation and its use in image analysis. Soft computing provides flexible information processing to handle real life ambiguous situations and achieve tractability, robustness low solution cost, and a closer resemblance to human decision making. Several systems are or have been developed: Fuzzy Reasoning Edge Detection (FRED), Fuzzy Reasoning Adaptive Thresholding (FRAT), Image enhancement techniques, and visual/pattern recognition. These systems are compared with examples that show the effectiveness of each. NASA applications that are reviewed are: Real-Time (RT) Anomaly Detection, Real-Time (RT) Moving Debris Detection and the Columbia Investigation. The RT anomaly detection reviewed the case of a damaged cable for the emergency egress system. The use of these techniques is further illustrated in the Columbia investigation with the location and detection of Foam debris. There are several applications in commercial usage: image enhancement, human screening and privacy protection, visual inspection, 3D heart visualization, tumor detections and x ray image enhancement.
ERIC Educational Resources Information Center
Hegelheimer, Volker; Reppert, Ketty; Broberg, Megan; Daisy, Brenda; Grgurovic, Maja; Middlebrooks, Katy; Liu, Sammi
2004-01-01
As more and more teacher preparation programs realize the need to include courses that deal with computer-assisted language learning, a crucial decision as to what is taught needs to be made, taking into consideration the various post-graduation goals ranging from teacher or teacher-trainer to researcher. Thus, the question of whether to go beyond…
Potential of Cognitive Computing and Cognitive Systems
NASA Astrophysics Data System (ADS)
Noor, Ahmed K.
2015-01-01
Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The cognitive assistants engage, individually or collectively, with humans through a combination of adaptive multimodal interfaces, and advanced visualization and navigation techniques. The realization of future cognitive environments requires the development of a cognitive innovation ecosystem for the engineering workforce. The continuously expanding major components of the ecosystem include integrated knowledge discovery and exploitation facilities (incorporating predictive and prescriptive big data analytics); novel cognitive modeling and visual simulation facilities; cognitive multimodal interfaces; and cognitive mobile and wearable devices. The ecosystem will provide timely, engaging, personalized / collaborative, learning and effective decision making. It will stimulate creativity and innovation, and prepare the participants to work in future cognitive enterprises and develop new cognitive products of increasing complexity. http://www.aee.odu.edu/cognitivecomp
NASA Astrophysics Data System (ADS)
Andreu, J.; Capilla, J.; Sanchís, E.
1996-04-01
This paper describes a generic decision-support system (DSS) which was originally designed for the planning stage of dicision-making associated with complex river basins. Subsequently, it was expanded to incorporate modules relating to the operational stage of decision-making. Computer-assisted design modules allow any complex water-resource system to be represented in graphical form, giving access to geographically referenced databases and knowledge bases. The modelling capability includes basin simulation and optimization modules, an aquifer flow modelling module and two modules for risk assessment. The Segura and Tagus river basins have been used as case studies in the development and validation phases. The value of this DSS is demonstrated by the fact that both River Basin Agencies currently use a version for the efficient management of their water resources.
Jibaja‐Weiss, Maria L.; Volk, Robert J.; Friedman, Lois C.; Granchi, Thomas S.; Neff, Nancy E.; Spann, Stephen J.; Robinson, Emily K.; Aoki, Noriaki; Robert Beck, J.
2006-01-01
Abstract Objective To report on the initial testing of a values clarification exercise utilizing a jewellery box within a computerized patient decision aid (CPtDA) designed to assist women in making a surgical breast cancer treatment decision. Design Pre‐post design, with patients interviewed after diagnosis, and then after completing the CPtDA sometime later at their preoperative visit. Sample Fifty‐one female patients, who are low literate and naïve computer users, newly diagnosed with early stage breast cancer from two urban public hospitals. Intervention A computerized decision aid that combines entertainment‐education (edutainment) with enhanced (factual) content. An interactive jewellery box is featured to assist women in: (1) recording and reflecting over issues of concern with possible treatments, (2) deliberating over surgery decision, and (3) communicating with physician and significant others. Outcomes Patients’ use of the jewellery box to store issues during completion of the CPtDA, and perceived clarity of values in making a treatment decision, as measured by a low literacy version of the Decisional Conflict Scale (DCS). Results Over half of the participants utilized the jewellery box to store issues they found concerning about the treatments. On average, users flagged over 13 issues of concern with the treatments. Scores on the DCS Uncertainty and Feeling Unclear about Values subscales were lower after the intervention compared to before the decision was made. Conclusions A values clarification exercise using an interactive jewellery box may be a promising method for promoting informed treatment decision making by low literacy breast cancer patients. PMID:16911136
Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing
NASA Astrophysics Data System (ADS)
Klems, Markus; Nimis, Jens; Tai, Stefan
On-demand provisioning of scalable and reliable compute services, along with a cost model that charges consumers based on actual service usage, has been an objective in distributed computing research and industry for a while. Cloud Computing promises to deliver on this objective: consumers are able to rent infrastructure in the Cloud as needed, deploy applications and store data, and access them via Web protocols on a pay-per-use basis. The acceptance of Cloud Computing, however, depends on the ability for Cloud Computing providers and consumers to implement a model for business value co-creation. Therefore, a systematic approach to measure costs and benefits of Cloud Computing is needed. In this paper, we discuss the need for valuation of Cloud Computing, identify key components, and structure these components in a framework. The framework assists decision makers in estimating Cloud Computing costs and to compare these costs to conventional IT solutions. We demonstrate by means of representative use cases how our framework can be applied to real world scenarios.
Use of a Computer Program for Advance Care Planning with African American Participants.
Markham, Sarah A; Levi, Benjamin H; Green, Michael J; Schubart, Jane R
2015-02-01
The authors wish to acknowledge the support and assistance of Dr. William Lawrence for his contribution to the M.A.UT model used in the decision aid, Making Your Wishes Known: Planning Your Medical Future (MYWK), Dr. Cheryl Dellasega for her leadership in focus group activities, Charles Sabatino for his review of legal aspects of MYWK, Dr. Robert Pearlman and his collaborative team for use of the advance care planning booklet "Your Life, Your Choices," Megan Whitehead for assistance in grant preparation and project organization, and the Instructional Media Development Center at the University of Wisconsin as well as JPL Integrated Communications for production and programming of MYWK. For various cultural and historical reasons, African Americans are less likely than Caucasians to engage in advance care planning (ACP) for healthcare decisions. This pilot study tested whether an interactive computer program could help overcome barriers to effective ACP among African Americans. African American adults were recruited from traditionally Black churches to complete an interactive computer program on ACP, pre-/post-questionnaires, and a follow-up phone interview. Eighteen adults (mean age =53.2 years, 83% female) completed the program without any problems. Knowledge about ACP significantly increased following the computer intervention (44.9% → 61.3%, p=0.0004), as did individuals' sense of self-determination. Participants were highly satisfied with the ACP process (9.4; 1 = not at all satisfied, 10 = extremely satisfied), and reported that the computer-generated advance directive accurately reflected their wishes (6.4; 1 = not at all accurate, 7 = extremely accurate). Follow-up phone interviews found that >80% of participants reported having shared their advance directives with family members and spokespeople. Preliminary evidence suggests that an interactive computer program can help African Americans engage in effective advance care planning, including creating an accurate advance directive document that will be shared with loved ones. © 2015 National Medical Association. Published by Elsevier Inc. All rights reserved.
Ruiz-España, Silvia; Arana, Estanislao; Moratal, David
2015-07-01
Computer-aided diagnosis (CAD) methods for detecting and classifying lumbar spine disease in Magnetic Resonance imaging (MRI) can assist radiologists to perform their decision-making tasks. In this paper, a CAD software has been developed able to classify and quantify spine disease (disc degeneration, herniation and spinal stenosis) in two-dimensional MRI. A set of 52 lumbar discs from 14 patients was used for training and 243 lumbar discs from 53 patients for testing in conventional two-dimensional MRI of the lumbar spine. To classify disc degeneration according to the gold standard, Pfirrmann classification, a method based on the measurement of disc signal intensity and structure was developed. A gradient Vector Flow algorithm was used to extract disc shape features and for detecting contour abnormalities. Also, a signal intensity method was used for segmenting and detecting spinal stenosis. Novel algorithms have also been developed to quantify the severity of these pathologies. Variability was evaluated by kappa (k) and intra-class correlation (ICC) statistics. Segmentation inaccuracy was below 1%. Almost perfect agreement, as measured by the k and ICC statistics, was obtained for all the analyzed pathologies: disc degeneration (k=0.81 with 95% CI=[0.75..0.88]) with a sensitivity of 95.8% and a specificity of 92.6%, disc herniation (k=0.94 with 95% CI=[0.87..1]) with a sensitivity of 60% and a specificity of 87.1%, categorical stenosis (k=0.94 with 95% CI=[0.90..0.98]) and quantitative stenosis (ICC=0.98 with 95% CI=[0.97..0.98]) with a sensitivity of 70% and a specificity of 81.7%. The proposed methods are reproducible and should be considered as a possible alternative when compared to reference standards. Copyright © 2015 Elsevier Ltd. All rights reserved.
van der Krieke, Lian; Emerencia, Ando C; Boonstra, Nynke; Wunderink, Lex; de Jonge, Peter; Sytema, Sjoerd
2013-10-07
Mental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes. This study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders. The study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation. In all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions on perceived involvement in medical decision making (COMRADE satisfaction with communication: F1,68=0.422, P=.52; COMRADE confidence in decision: F1,67=0.086, P=.77). In addition, results of the process evaluation suggest that the intervention did not optimally fit in with routine practice of the participating teams. The development of electronic decision aids to facilitate shared medical decision making is encouraged and many people with a psychotic disorder can work with them. This holds for both first-episode patients and long-term care patients, although the latter group might need more assistance. However, results of this paper could not support the assumption that the use of electronic decision aids increases patient involvement in medical decision making. This may be because of weak implementation of the study protocol and a low response rate.
Personal data assistants: using new technology to enhance nursing practice.
Lewis, Judith A; Sommers, Catherine O
2003-01-01
This article explains how the new technology of personal data assistants can be used to enhance and augment comprehensive nursing care. Nurses are constantly challenged in their need for current, reliable, and accurate information at the point of patient care. Professional books and journals, by the very nature of their print format, have been prepared long before they can be actually used in practice. More current information is available from the World Wide Web, but it is often impractical for a nurse to access a computer during a patient encounter. Personal data assistants [PDAs] allow clinicians to access and document absolutely current information at the moment the patient is being seen. There are many general applications for PDAs that nurses might use such as keeping electronic calendars, address books, and reminder lists. In addition, however, there are even more actual healthcare applications, including patient tracking systems, access to pharmacologic databases, and a variety of clinical decision-making support tools. This article describes the wide variety of PDAs, along with the factors a nurse should consider in the decision of whether to purchase a PDA, and which type of device is best suited for which application.
An Integrated Theory of Attention and Decision Making in Visual Signal Detection
ERIC Educational Resources Information Center
Smith, Philip L.; Ratcliff, Roger
2009-01-01
The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in…
Computer-assisted detection of epileptiform focuses on SPECT images
NASA Astrophysics Data System (ADS)
Grzegorczyk, Dawid; Dunin-Wąsowicz, Dorota; Mulawka, Jan J.
2010-09-01
Epilepsy is a common nervous system disease often related to consciousness disturbances and muscular spasm which affects about 1% of the human population. Despite major technological advances done in medicine in the last years there was no sufficient progress towards overcoming it. Application of advanced statistical methods and computer image analysis offers the hope for accurate detection and later removal of an epileptiform focuses which are the cause of some types of epilepsy. The aim of this work was to create a computer system that would help to find and diagnose disorders of blood circulation in the brain This may be helpful for the diagnosis of the epileptic seizures onset in the brain.
Evaluating Imaging and Computer-aided Detection and Diagnosis Devices at the FDA
Gallas, Brandon D.; Chan, Heang-Ping; D’Orsi, Carl J.; Dodd, Lori E.; Giger, Maryellen L.; Gur, David; Krupinski, Elizabeth A.; Metz, Charles E.; Myers, Kyle J.; Obuchowski, Nancy A.; Sahiner, Berkman; Toledano, Alicia Y.; Zuley, Margarita L.
2017-01-01
This report summarizes the Joint FDA-MIPS Workshop on Methods for the Evaluation of Imaging and Computer-Assist Devices. The purpose of the workshop was to gather information on the current state of the science and facilitate consensus development on statistical methods and study designs for the evaluation of imaging devices to support US Food and Drug Administration submissions. Additionally, participants expected to identify gaps in knowledge and unmet needs that should be addressed in future research. This summary is intended to document the topics that were discussed at the meeting and disseminate the lessons that have been learned through past studies of imaging and computer-aided detection and diagnosis device performance. PMID:22306064
Oshima, Toru; Hayashida, Mitsumasa; Ohtani, Maki; Hashimoto, Manabu; Takahashi, Satoshi; Ishiyama, Koichi; Otani, Takahiro; Koga, Makoto; Sugawara, Makoto; Mimasaka, Sohtaro
2014-07-01
Although spine injuries are not always detectable on postmortem computed tomography (PMCT), spinal hyperostosis, an important risk factor for spine injury, is relatively easily detectable on PMCT. We therefore examined the utility of the detection of spinal hyperostosis on PMCT as an indicator of spine injury. Full-body PMCT images of 88 autopsy cases with a bruise on the face or forehead but no identifiable skull fracture were reviewed prior to autopsy for the identification and classification of spinal hyperostosis. Spine injuries were observed in 56.0% of cases with spinal hyperostosis and 1.6% of cases without spinal hyperostosis. Among the cases with spinal hyperostosis, spine injuries were observed in 66.7% of cases at stage 2 or 3 and in 88.9% of cases at stage 3. Spine injuries were diagnosed on PMCT in 33.3% of cases prior to autopsy. A significant association was found between spinal hyperostosis and presence of spine injury that cannot be detected on PMCT, indicating that the identification of spinal hyperostosis on PMCT may assist in detecting spine injuries. This finding suggests that investigation of the presence of spine injury based on the identification of spinal hyperostosis on PMCT may assist in determining the correct cause of death by autopsy. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Earth observations and global change decision making: A special bibliography, 1991
NASA Technical Reports Server (NTRS)
1991-01-01
The first section of the bibliography contains 294 bibliographic citations and abstracts of relevant reports, articles, and documents announced in 'Scientific and Technical Aerospace Reports (STAR)' and 'International Aerospace Abstracts (IAA)'. These abstracts are categorized by the following major subject divisions: aeronautics, astronautics, chemistry and materials, engineering, geosciences, life sciences, mathematical and computer sciences, physics, social sciences, space sciences and general. Following the abstract section, seven indexes are provided for further assistance.
Statistical behavior of ten million experimental detection limits
NASA Astrophysics Data System (ADS)
Voigtman, Edward; Abraham, Kevin T.
2011-02-01
Using a lab-constructed laser-excited fluorimeter, together with bootstrapping methodology, the authors have generated many millions of experimental linear calibration curves for the detection of rhodamine 6G tetrafluoroborate in ethanol solutions. The detection limits computed from them are in excellent agreement with both previously published theory and with comprehensive Monte Carlo computer simulations. Currie decision levels and Currie detection limits, each in the theoretical, chemical content domain, were found to be simply scaled reciprocals of the non-centrality parameter of the non-central t distribution that characterizes univariate linear calibration curves that have homoscedastic, additive Gaussian white noise. Accurate and precise estimates of the theoretical, content domain Currie detection limit for the experimental system, with 5% (each) probabilities of false positives and false negatives, are presented.
Schimmer, C; Hamouda, K; Oezkur, M; Sommer, S-P; Leistner, M; Leyh, R
2016-03-01
Ethical and medical criteria in the decision-making process of withholding or withdrawal of life support therapy in critically ill patients present a great challenge in intensive care medicine. The purpose of this work was to assess medical and ethical criteria that influence the decision-making process for changing the aim of therapy in critically ill cardiac surgery patients. A questionnaire was distributed to all German cardiac surgery centers (n = 79). All clinical directors, intensive care unit (ICU) consultants and ICU head nurses were asked to complete questionnaires (n = 237). In all, 86 of 237 (36.3 %) questionnaires were returned. Medical reasons which influence the decision-making process for changing the aim of therapy were cranial computed tomography (cCT) with poor prognosis (91.9 %), multi-organ failure (70.9 %), and failure of assist device therapy (69.8 %). Concerning ethical reasons, poor expected quality of life (48.8 %) and the presumed patient's wishes (40.7 %) were reported. There was a significant difference regarding the perception of the three different professional groups concerning medical and ethical criteria as well as the involvement in the decision-making process. In critically ill cardiac surgery patients, medical reasons which influence the decision-making process for changing the aim of therapy included cCT with poor prognosis, multi-organ failure, and failure of assist device therapy. Further studies are mandatory in order to be able to provide adequate answers to this difficult topic.
Kabakyenga, Jerome K.; Östergren, Per-Olof; Turyakira, Eleanor; Pettersson, Karen Odberg
2012-01-01
Introduction Assistance by skilled birth attendants (SBAs) during childbirth is one of the strategies aimed at reducing maternal morbidity and mortality in low-income countries. However, the relationship between birth preparedness and decision-making on location of birth and assistance by skilled birth attendants in this context is not well studied. The aim of this study was to assess the influence of birth preparedness practices and decision-making and assistance by SBAs among women in south-western Uganda. Methods Community survey methods were used to identify 759 recently delivered women from 120 villages in rural Mbarara district. Interviewer-administered questionnaires were used to collect data. Logistic regression analyses were conducted to assess the relationship between birth preparedness, decision-making on location of birth and assistance by SBAs. Results 35% of the women had been prepared for childbirth and the prevalence of assistance by SBAs in the sample was 68%. The final decision regarding location of birth was made by the woman herself (36%), the woman with spouse (56%) and the woman with relative/friend (8%). The relationships between birth preparedness and women decision-making on location of birth in consultation with spouse/friends/relatives and choosing assistance by SBAs showed statistical significance which persisted after adjusting for possible confounders (OR 1.5, 95% CI: 1.0–2.4) and (OR 4.4, 95% CI: 3.0–6.7) respectively. Education, household assets and birth preparedness showed clear synergistic effect on the relationship between decision-maker on location of birth and assistance by SBAs. Other factors which showed statistical significant relationships with assistance by SBAs were ANC attendance, parity and residence. Conclusion Women’s decision-making on location of birth in consultation with spouse/friends/relatives and birth preparedness showed significant effect on choosing assistance by SBAs at birth. Education and household assets ownership showed a synergistic effect on the relationship between the decision-maker and assistance by SBAs. PMID:22558214
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tourassi, Georgia D.; Harrawood, Brian; Singh, Swatee
2007-08-15
We have previously presented a knowledge-based computer-assisted detection (KB-CADe) system for the detection of mammographic masses. The system is designed to compare a query mammographic region with mammographic templates of known ground truth. The templates are stored in an adaptive knowledge database. Image similarity is assessed with information theoretic measures (e.g., mutual information) derived directly from the image histograms. A previous study suggested that the diagnostic performance of the system steadily improves as the knowledge database is initially enriched with more templates. However, as the database increases in size, an exhaustive comparison of the query case with each stored templatemore » becomes computationally burdensome. Furthermore, blind storing of new templates may result in redundancies that do not necessarily improve diagnostic performance. To address these concerns we investigated an entropy-based indexing scheme for improving the speed of analysis and for satisfying database storage restrictions without compromising the overall diagnostic performance of our KB-CADe system. The indexing scheme was evaluated on two different datasets as (i) a search mechanism to sort through the knowledge database, and (ii) a selection mechanism to build a smaller, concise knowledge database that is easier to maintain but still effective. There were two important findings in the study. First, entropy-based indexing is an effective strategy to identify fast a subset of templates that are most relevant to a given query. Only this subset could be analyzed in more detail using mutual information for optimized decision making regarding the query. Second, a selective entropy-based deposit strategy may be preferable where only high entropy cases are maintained in the knowledge database. Overall, the proposed entropy-based indexing scheme was shown to reduce the computational cost of our KB-CADe system by 55% to 80% while maintaining the system's diagnostic performance.« less
Dynamic Decision Making in Complex Task Environments: Principles and Neural Mechanisms
2013-03-01
Dynamical models of cognition . Mathematical models of mental processes. Human performance optimization. U U U U Dr. Jay Myung 703-696-8487 Reset 1...we have continued to develop a neurodynamic theory of decision making, using a combination of computational and experimental approaches, to address...a long history in the field of human cognitive psychology. The theoretical foundations of this research can be traced back to signal detection
Using Unix system auditing for detecting network intrusions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Christensen, M.J.
1993-03-01
Intrusion Detection Systems (IDSs) are designed to detect actions of individuals who use computer resources without authorization as well as legitimate users who exceed their privileges. This paper describes a novel approach to IDS research, namely a decision aiding approach to intrusion detection. The introduction of a decision tree represents the logical steps necessary to distinguish and identify different types of attacks. This tool, the Intrusion Decision Aiding Tool (IDAT), utilizes IDS-based attack models and standard Unix audit data. Since attacks have certain characteristics and are based on already developed signature attack models, experienced and knowledgeable Unix system administrators knowmore » what to look for in system audit logs to determine if a system has been attacked. Others, however, are usually less able to recognize common signatures of unauthorized access. Users can traverse the tree using available audit data displayed by IDAT and general knowledge they possess to reach a conclusion regarding suspicious activity. IDAT is an easy-to-use window based application that gathers, analyzes, and displays pertinent system data according to Unix attack characteristics. IDAT offers a more practical approach and allows the user to make an informed decision regarding suspicious activity.« less
NASA Astrophysics Data System (ADS)
Lammers, Craig; McGraw, Robert M.; Steinman, Jeffrey S.
2005-05-01
Technological advances and emerging threats reduce the time between target detection and action to an order of a few minutes. To effectively assist with the decision-making process, C4I decision support tools must quickly and dynamically predict and assess alternative Courses Of Action (COAs) to assist Commanders in anticipating potential outcomes. These capabilities can be provided through the faster-than-real-time predictive simulation of plans that are continuously re-calibrating with the real-time picture. This capability allows decision-makers to assess the effects of re-tasking opportunities, providing the decision-maker with tremendous freedom to make time-critical, mid-course decisions. This paper presents an overview and demonstrates the use of a software infrastructure that supports DSAP capabilities. These DSAP capabilities are demonstrated through the use of a Multi-Replication Framework that supports (1) predictivie simulations using JSAF (Joint Semi-Automated Forces); (2) real-time simulation, also using JSAF, as a state estimation mechanism; and, (3) real-time C4I data updates through TBMCS (Theater Battle Management Core Systems). This infrastructure allows multiple replications of a simulation to be executed simultaneously over a grid faster-than-real-time, calibrated with live data feeds. A cost evaluator mechanism analyzes potential outcomes and prunes simulations that diverge from the real-time picture. In particular, this paper primarily serves to walk a user through the process for using the Multi-Replication Framework providing an enhanced decision aid.
Automatic violence detection in digital movies
NASA Astrophysics Data System (ADS)
Fischer, Stephan
1996-11-01
Research on computer-based recognition of violence is scant. We are working on the automatic recognition of violence in digital movies, a first step towards the goal of a computer- assisted system capable of protecting children against TV programs containing a great deal of violence. In the video domain a collision detection and a model-mapping to locate human figures are run, while the creation and comparison of fingerprints to find certain events are run int he audio domain. This article centers on the recognition of fist- fights in the video domain and on the recognition of shots, explosions and cries in the audio domain.
Tanaka, M; Nakazono, S; Matsuno, H; Tsujimoto, H; Kitamura, Y; Miyano, S
2000-01-01
We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.
A computational relationship between thalamic sensory neural responses and contrast perception.
Jiang, Yaoguang; Purushothaman, Gopathy; Casagrande, Vivien A
2015-01-01
Uncovering the relationship between sensory neural responses and perceptual decisions remains a fundamental problem in neuroscience. Decades of experimental and modeling work in the sensory cortex have demonstrated that a perceptual decision pool is usually composed of tens to hundreds of neurons, the responses of which are significantly correlated not only with each other, but also with the behavioral choices of an animal. Few studies, however, have measured neural activity in the sensory thalamus of awake, behaving animals. Therefore, it remains unclear how many thalamic neurons are recruited and how the information from these neurons is pooled at subsequent cortical stages to form a perceptual decision. In a previous study we measured neural activity in the macaque lateral geniculate nucleus (LGN) during a two alternative forced choice (2AFC) contrast detection task, and found that single LGN neurons were significantly correlated with the monkeys' behavioral choices, despite their relatively poor contrast sensitivity and a lack of overall interneuronal correlations. We have now computationally tested a number of specific hypotheses relating these measured LGN neural responses to the contrast detection behavior of the animals. We modeled the perceptual decisions with different numbers of neurons and using a variety of pooling/readout strategies, and found that the most successful model consisted of about 50-200 LGN neurons, with individual neurons weighted differentially according to their signal-to-noise ratios (quantified as d-primes). These results supported the hypothesis that in contrast detection the perceptual decision pool consists of multiple thalamic neurons, and that the response fluctuations in these neurons can influence contrast perception, with the more sensitive thalamic neurons likely to exert a greater influence.
Variable size computer-aided detection prompts and mammography film reader decisions
Gilbert, Fiona J; Astley, Susan M; Boggis, Caroline RM; McGee, Magnus A; Griffiths, Pamela M; Duffy, Stephen W; Agbaje, Olorunsola F; Gillan, Maureen GC; Wilson, Mary; Jain, Anil K; Barr, Nicola; Beetles, Ursula M; Griffiths, Miriam A; Johnson, Jill; Roberts, Rita M; Deans, Heather E; Duncan, Karen A; Iyengar, Geeta
2008-01-01
Introduction The purpose of the present study was to investigate the effect of computer-aided detection (CAD) prompts on reader behaviour in a large sample of breast screening mammograms by analysing the relationship of the presence and size of prompts to the recall decision. Methods Local research ethics committee approval was obtained; informed consent was not required. Mammograms were obtained from women attending routine mammography at two breast screening centres in 1996. Films, previously double read, were re-read by a different reader using CAD. The study material included 315 cancer cases comprising all screen-detected cancer cases, all subsequent interval cancers and 861 normal cases randomly selected from 10,267 cases. Ground truth data were used to assess the efficacy of CAD prompting. Associations between prompt attributes and tumour features or reader recall decisions were assessed by chi-squared tests. Results There was a highly significant relationship between prompting and a decision to recall for cancer cases and for a random sample of normal cases (P < 0.001). Sixty-four per cent of all cases contained at least one CAD prompt. In cancer cases, larger prompts were more likely to be recalled (P = 0.02) for masses but there was no such association for calcifications (P = 0.9). In a random sample of 861 normal cases, larger prompts were more likely to be recalled (P = 0.02) for both mass and calcification prompts. Significant associations were observed with prompting and breast density (p = 0.009) for cancer cases but not for normal cases (P = 0.05). Conclusions For both normal cases and cancer cases, prompted mammograms were more likely to be recalled and the prompt size was also associated with a recall decision. PMID:18724867
Variable size computer-aided detection prompts and mammography film reader decisions.
Gilbert, Fiona J; Astley, Susan M; Boggis, Caroline Rm; McGee, Magnus A; Griffiths, Pamela M; Duffy, Stephen W; Agbaje, Olorunsola F; Gillan, Maureen Gc; Wilson, Mary; Jain, Anil K; Barr, Nicola; Beetles, Ursula M; Griffiths, Miriam A; Johnson, Jill; Roberts, Rita M; Deans, Heather E; Duncan, Karen A; Iyengar, Geeta
2008-01-01
The purpose of the present study was to investigate the effect of computer-aided detection (CAD) prompts on reader behaviour in a large sample of breast screening mammograms by analysing the relationship of the presence and size of prompts to the recall decision. Local research ethics committee approval was obtained; informed consent was not required. Mammograms were obtained from women attending routine mammography at two breast screening centres in 1996. Films, previously double read, were re-read by a different reader using CAD. The study material included 315 cancer cases comprising all screen-detected cancer cases, all subsequent interval cancers and 861 normal cases randomly selected from 10,267 cases. Ground truth data were used to assess the efficacy of CAD prompting. Associations between prompt attributes and tumour features or reader recall decisions were assessed by chi-squared tests. There was a highly significant relationship between prompting and a decision to recall for cancer cases and for a random sample of normal cases (P < 0.001). Sixty-four per cent of all cases contained at least one CAD prompt. In cancer cases, larger prompts were more likely to be recalled (P = 0.02) for masses but there was no such association for calcifications (P = 0.9). In a random sample of 861 normal cases, larger prompts were more likely to be recalled (P = 0.02) for both mass and calcification prompts. Significant associations were observed with prompting and breast density (p = 0.009) for cancer cases but not for normal cases (P = 0.05). For both normal cases and cancer cases, prompted mammograms were more likely to be recalled and the prompt size was also associated with a recall decision.
Frazier, T; Yount, K M
2017-02-01
Detecting sensitive health information in clinical settings is of scientific and practical importance. The purpose of this study was to determine whether mode of screening influenced disclosure of intimate partner violence (IPV) in patterns similar to other forms of sensitive information. This cross sectional study was designed to compare effects of face-to-face vs computer self-assessment for sensitive health information on disclosure rates. Multivariate logistic regression was used for the analysis. Data were collected in 2012 from 639 eligible African American consenting women receiving services in women, infants and children (WIC) clinics. Women were randomized to complete assessments of sensitive exposures via computer-assisted self-interview (CASI) or face-to-face interview (FTFI). Those with complete information were included in the analysis (n = 616). Of 39 sensitive health exposures, reporting was higher for FTFI than CASI for exposure to IPV (7 of 7 outcomes), tobacco use (2 of 3 outcomes) and reproductive health care (2 of 3 outcomes). For example, face-to-face improved disclosure of IPV in the last year (adjusted odds ratios [aOR] = 2.27; 95% CI = 1.60-3.21) and any drug, tobacco or alcohol in the last week (aOR = 1.39; 95% CI = 1.00-1.93). Trained personnel may enhance disclosure above computer-based assessments for IPV for African American women receiving public assistance through The Special Supplemental Nutrition Program for Women, Infants and Children (WIC) Propensities to disclose sexual health behaviour and drug use by CASI may not apply to IPV in this population. The context and personal motivations influence women's decision to disclose IPV. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
Evaluation of technology to identify and assess overweight children and adolescents.
Gance-Cleveland, Bonnie; Gilbert, Lynn H; Kopanos, Taynin; Gilbert, Kevin C
2010-01-01
The current obesity epidemic has produced a generation of children that may be the first to have a life expectancy shorter than their parents. To address the obesity epidemic, experts have published recommendations for providers. Research suggests the publication of guidelines may not change provider behavior. This study evaluates computer assistance for implementing obesity guidelines in school-based health centers. Significant improvements in identification and assessment of obesity in children with technology support were noted. Computer decision support shows promise for promoting the implementation of current recommendations by supporting providers in identifying, assessing, and providing tailored recommendations for children at risk of obesity.
Summerfield, Christopher; Tsetsos, Konstantinos
2012-01-01
Investigation into the neural and computational bases of decision-making has proceeded in two parallel but distinct streams. Perceptual decision-making (PDM) is concerned with how observers detect, discriminate, and categorize noisy sensory information. Economic decision-making (EDM) explores how options are selected on the basis of their reinforcement history. Traditionally, the sub-fields of PDM and EDM have employed different paradigms, proposed different mechanistic models, explored different brain regions, disagreed about whether decisions approach optimality. Nevertheless, we argue that there is a common framework for understanding decisions made in both tasks, under which an agent has to combine sensory information (what is the stimulus) with value information (what is it worth). We review computational models of the decision process typically used in PDM, based around the idea that decisions involve a serial integration of evidence, and assess their applicability to decisions between good and gambles. Subsequently, we consider the contribution of three key brain regions - the parietal cortex, the basal ganglia, and the orbitofrontal cortex (OFC) - to perceptual and EDM, with a focus on the mechanisms by which sensory and reward information are integrated during choice. We find that although the parietal cortex is often implicated in the integration of sensory evidence, there is evidence for its role in encoding the expected value of a decision. Similarly, although much research has emphasized the role of the striatum and OFC in value-guided choices, they may play an important role in categorization of perceptual information. In conclusion, we consider how findings from the two fields might be brought together, in order to move toward a general framework for understanding decision-making in humans and other primates.
Summerfield, Christopher; Tsetsos, Konstantinos
2012-01-01
Investigation into the neural and computational bases of decision-making has proceeded in two parallel but distinct streams. Perceptual decision-making (PDM) is concerned with how observers detect, discriminate, and categorize noisy sensory information. Economic decision-making (EDM) explores how options are selected on the basis of their reinforcement history. Traditionally, the sub-fields of PDM and EDM have employed different paradigms, proposed different mechanistic models, explored different brain regions, disagreed about whether decisions approach optimality. Nevertheless, we argue that there is a common framework for understanding decisions made in both tasks, under which an agent has to combine sensory information (what is the stimulus) with value information (what is it worth). We review computational models of the decision process typically used in PDM, based around the idea that decisions involve a serial integration of evidence, and assess their applicability to decisions between good and gambles. Subsequently, we consider the contribution of three key brain regions – the parietal cortex, the basal ganglia, and the orbitofrontal cortex (OFC) – to perceptual and EDM, with a focus on the mechanisms by which sensory and reward information are integrated during choice. We find that although the parietal cortex is often implicated in the integration of sensory evidence, there is evidence for its role in encoding the expected value of a decision. Similarly, although much research has emphasized the role of the striatum and OFC in value-guided choices, they may play an important role in categorization of perceptual information. In conclusion, we consider how findings from the two fields might be brought together, in order to move toward a general framework for understanding decision-making in humans and other primates. PMID:22654730
Olin, Emma; von Schreeb, Johan
2014-01-01
Background: International humanitarian assistance is essential for disaster-affected populations, particularly in resource scarce settings. To target such assistance, needs assessments are required. According to internationally endorsed principles, donor governments should provide funding for humanitarian assistance based on need. Aim: The aim of this study is to explore a major donor’s use of needs assessment data in decision-making for allocations of funds for health-related humanitarian assistance contributions. Setting: This is a case study of the Swedish International Development Cooperation Agency (Sida), a major and respected international donor of humanitarian assistance. Methods: To explore Sida’s use of needs assessment data in practice for needs-based allocations, we reviewed all decision documents and assessment memoranda for humanitarian assistance contributions for 2012 using content analysis; this was followed by interviews with key personnel at Sida. Results: Our document analysis found that needs assessment data was not systematically included in Sida’s assessment memoranda and decision documents. In the interviews, we observed various descriptions of the concept of needs assessments, the importance of contextual influences as well as previous collaborations with implementing humanitarian assistance organizations. Our findings indicate that policies guiding funding decisions on humanitarian assistance need to be matched with available needs assessment data and that terminologies and concepts have to be clearly defined. Conclusion: Based on the document analysis and the interviews, it is unclear how well Sida used needs assessment data for decisions to allocate funds. However, although our observations show that needs assessments are seldom used in decision making, Sida’s use of needs assessments has improved compared to a previous study. To improve project funds allocations based on needs assessment data, it will be critical to develop distinct frameworks for allocation distributions based on needs assessment and clear definitions, measurements and interpretations of needs. Key words: Needs assessment, humanitarian assistance, disasters, donor decision-making PMID:24894417
PSYCHE: An Object-Oriented Approach to Simulating Medical Education
Mullen, Jamie A.
1990-01-01
Traditional approaches to computer-assisted instruction (CAI) do not provide realistic simulations of medical education, in part because they do not utilize heterogeneous knowledge bases for their source of domain knowledge. PSYCHE, a CAI program designed to teach hypothetico-deductive psychiatric decision-making to medical students, uses an object-oriented implementation of an intelligent tutoring system (ITS) to model the student, domain expert, and tutor. It models the transactions between the participants in complex transaction chains, and uses heterogeneous knowledge bases to represent both domain and procedural knowledge in clinical medicine. This object-oriented approach is a flexible and dynamic approach to modeling, and represents a potentially valuable tool for the investigation of medical education and decision-making.
Markerless laser registration in image-guided oral and maxillofacial surgery.
Marmulla, Rüdiger; Lüth, Tim; Mühling, Joachim; Hassfeld, Stefan
2004-07-01
The use of registration markers in computer-assisted surgery is combined with high logistic costs and efforts. Markerless patient registration using laser scan surface registration techniques is a new challenging method. The present study was performed to evaluate the clinical accuracy in finding defined target points within the surgical site after markerless patient registration in image-guided oral and maxillofacial surgery. Twenty consecutive patients with different cranial diseases were scheduled for computer-assisted surgery. Data set alignment between the surgical site and the computed tomography (CT) data set was performed by markerless laser scan surface registration of the patient's face. Intraoral rigidly attached registration markers were used as target points, which had to be detected by an infrared pointer. The Surgical Segment Navigator SSN++ has been used for all procedures. SSN++ is an investigative product based on the SSN system that had previously been developed by the presenting authors with the support of Carl Zeiss (Oberkochen, Germany). SSN++ is connected to a Polaris infrared camera (Northern Digital, Waterloo, Ontario, Canada) and to a Minolta VI 900 3D digitizer (Tokyo, Japan) for high-resolution laser scanning. Minimal differences in shape between the laser scan surface and the surface generated from the CT data set could be detected. Nevertheless, high-resolution laser scan of the skin surface allows for a precise patient registration (mean deviation 1.1 mm, maximum deviation 1.8 mm). Radiation load, logistic costs, and efforts arising from the planning of computer-assisted surgery of the head can be reduced because native (markerless) CT data sets can be used for laser scan-based surface registration.
Kenneth L. Clark; Nicholas Skowronski; John Hom; Matthew Duveneck; Yude Pan; Stephen Van Tuyl; Jason Cole; Matthew Patterson; Stephen Maurer
2009-01-01
Our goal is to assist the New Jersey Forest Fire Service and federal wildland fire managers in the New Jersey Pine Barrens evaluate where and when to conduct hazardous fuel reduction treatments. We used remotely sensed LIDAR (Light Detection and Ranging System) data and field sampling to estimate fuel loads and consumption during prescribed fire treatments. This...
29 CFR 1910.7 - Definition and requirements for a nationally recognized testing laboratory.
Code of Federal Regulations, 2010 CFR
2010-07-01
... prejudice, at any time prior to the final decision by the Assistant Secretary in paragraph I.B.7.c. of this... writing by the close of the comment period. 6. Action after public comment—a. Final decision by Assistant... comment period. b. Public announcement. A copy of the Assistant Secretary's final decision will be...
Dissociation in decision bias mechanism between probabilistic information and previous decision
Kaneko, Yoshiyuki; Sakai, Katsuyuki
2015-01-01
Target detection performance is known to be influenced by events in the previous trials. It has not been clear, however, whether this bias effect is due to the previous sensory stimulus, motor response, or decision. Also it remains open whether or not the previous trial effect emerges via the same mechanism as the effect of knowledge about the target probability. In the present study, we asked normal human subjects to make a decision about the presence or absence of a visual target. We presented a pre-cue indicating the target probability before the stimulus, and also a decision-response mapping cue after the stimulus so as to tease apart the effect of decision from that of motor response. We found that the target detection performance was significantly affected by the probability cue in the current trial and also by the decision in the previous trial. While the information about the target probability modulated the decision criteria, the previous decision modulated the sensitivity to target-relevant sensory signals (d-prime). Using functional magnetic resonance imaging (fMRI), we also found that activation in the left intraparietal sulcus (IPS) was decreased when the probability cue indicated a high probability of the target. By contrast, activation in the right inferior frontal gyrus (IFG) was increased when the subjects made a target-present decision in the previous trial, but this change was observed specifically when the target was present in the current trial. Activation in these regions was associated with individual-difference in the decision computation parameters. We argue that the previous decision biases the target detection performance by modulating the processing of target-selective information, and this mechanism is distinct from modulation of decision criteria due to expectation of a target. PMID:25999844
Detection of benign prostatic hyperplasia nodules in T2W MR images using fuzzy decision forest
NASA Astrophysics Data System (ADS)
Lay, Nathan; Freeman, Sabrina; Turkbey, Baris; Summers, Ronald M.
2016-03-01
Prostate cancer is the second leading cause of cancer-related death in men MRI has proven useful for detecting prostate cancer, and CAD may further improve detection. One source of false positives in prostate computer-aided diagnosis (CAD) is the presence of benign prostatic hyperplasia (BPH) nodules. These nodules have a distinct appearance with a pseudo-capsule on T2 weighted MR images but can also resemble cancerous lesions in other sequences such as the ADC or high B-value images. Describing their appearance with hand-crafted heuristics (features) that also exclude the appearance of cancerous lesions is challenging. This work develops a method based on fuzzy decision forests to automatically learn discriminative features for the purpose of BPH nodule detection in T2 weighted images for the purpose of improving prostate CAD systems.
Selecting Power-Efficient Signal Features for a Low-Power Fall Detector.
Wang, Changhong; Redmond, Stephen J; Lu, Wei; Stevens, Michael C; Lord, Stephen R; Lovell, Nigel H
2017-11-01
Falls are a serious threat to the health of older people. A wearable fall detector can automatically detect the occurrence of a fall and alert a caregiver or an emergency response service so they may deliver immediate assistance, improving the chances of recovering from fall-related injuries. One constraint of such a wearable technology is its limited battery life. Thus, minimization of power consumption is an important design concern, all the while maintaining satisfactory accuracy of the fall detection algorithms implemented on the wearable device. This paper proposes an approach for selecting power-efficient signal features such that the minimum desirable fall detection accuracy is assured. Using data collected in simulated falls, simulated activities of daily living, and real free-living trials, all using young volunteers, the proposed approach selects four features from a set of ten commonly used features, providing a power saving of 75.3%, while limiting the error rate of a binary classification decision tree fall detection algorithm to 7.1%.Falls are a serious threat to the health of older people. A wearable fall detector can automatically detect the occurrence of a fall and alert a caregiver or an emergency response service so they may deliver immediate assistance, improving the chances of recovering from fall-related injuries. One constraint of such a wearable technology is its limited battery life. Thus, minimization of power consumption is an important design concern, all the while maintaining satisfactory accuracy of the fall detection algorithms implemented on the wearable device. This paper proposes an approach for selecting power-efficient signal features such that the minimum desirable fall detection accuracy is assured. Using data collected in simulated falls, simulated activities of daily living, and real free-living trials, all using young volunteers, the proposed approach selects four features from a set of ten commonly used features, providing a power saving of 75.3%, while limiting the error rate of a binary classification decision tree fall detection algorithm to 7.1%.
Dynamic remapping decisions in multi-phase parallel computations
NASA Technical Reports Server (NTRS)
Nicol, D. M.; Reynolds, P. F., Jr.
1986-01-01
The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.
Iwazawa, J; Ohue, S; Hashimoto, N; Mitani, T
2014-02-01
To compare the accuracy of computer software analysis using three different target-definition protocols to detect tumour feeder vessels for transarterial chemoembolization of hepatocellular carcinoma. C-arm computed tomography (CT) data were analysed for 81 tumours from 57 patients who had undergone chemoembolization using software-assisted detection of tumour feeders. Small, medium, and large-sized targets were manually defined for each tumour. The tumour feeder was verified when the target tumour was enhanced on selective C-arm CT of the investigated vessel during chemoembolization. The sensitivity, specificity, and accuracy of the three protocols were evaluated and compared. One hundred and eight feeder vessels supplying 81 lesions were detected. The sensitivity of the small, medium, and large target protocols was 79.8%, 91.7%, and 96.3%, respectively; specificity was 95%, 88%, and 50%, respectively; and accuracy was 87.5%, 89.9%, and 74%, respectively. The sensitivity was significantly higher for the medium (p = 0.003) and large (p < 0.001) target protocols than for the small target protocol. The specificity and accuracy were higher for the small (p < 0.001 and p < 0.001, respectively) and medium (p < 0.001 and p < 0.001, respectively) target protocols than for the large target protocol. The overall accuracy of software-assisted automated feeder analysis in transarterial chemoembolization for hepatocellular carcinoma is affected by the target definition size. A large target definition increases sensitivity and decreases specificity in detecting tumour feeders. A target size equivalent to the tumour size most accurately predicts tumour feeders. Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
2015-04-01
Type 2 diabetes (7-8). Hypertension is one of the most common co-morbidities associated with DM and substantially contributes to the macrovascular...challenged when attempting to upload their glucose data. Access to the patient portal , Diabetes Mellitus Everywhere (DME) in CDMP required installation of...antihypertensive treatment on cardiovascular disease risk in older diabetic patients with isolated systolic hypertension . Systolic hypertension in
Computer-Assisted Visual Search/Decision Aids as a Training Tool for Mammography
1999-07-01
display of a digital mammogram that compensates for the display brightness, the ambient light and the useful range of pixel intensities in the image...described here extends the work of Liu and Nodine (7) to include adjusting the gray-scale transform for ambient illumination and adjusting the mammogram...visible" disk in each band. The observer’s responses are affected by the display contrast and the ambient room lighting. The contrast of each indicated
Data acquisition and path selection decision making for an autonomous roving vehicle
NASA Technical Reports Server (NTRS)
Frederick, D. K.; Shen, C. N.; Yerazunis, S. W.
1976-01-01
Problems related to the guidance of an autonomous rover for unmanned planetary exploration were investigated. Topics included in these studies were: simulation on an interactive graphics computer system of the Rapid Estimation Technique for detection of discrete obstacles; incorporation of a simultaneous Bayesian estimate of states and inputs in the Rapid Estimation Scheme; development of methods for estimating actual laser rangefinder errors and their application to date provided by Jet Propulsion Laboratory; and modification of a path selection system simulation computer code for evaluation of a hazard detection system based on laser rangefinder data.
Second CLIPS Conference Proceedings, volume 1
NASA Technical Reports Server (NTRS)
Giarratano, Joseph (Editor); Culbert, Christopher J. (Editor)
1991-01-01
Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems.
Mickan, Sharon; Tilson, Julie K; Atherton, Helen; Roberts, Nia Wyn; Heneghan, Carl
2013-10-28
Handheld computers and mobile devices provide instant access to vast amounts and types of useful information for health care professionals. Their reduced size and increased processing speed has led to rapid adoption in health care. Thus, it is important to identify whether handheld computers are actually effective in clinical practice. A scoping review of systematic reviews was designed to provide a quick overview of the documented evidence of effectiveness for health care professionals using handheld computers in their clinical work. A detailed search, sensitive for systematic reviews was applied for Cochrane, Medline, EMBASE, PsycINFO, Allied and Complementary Medicine Database (AMED), Global Health, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases. All outcomes that demonstrated effectiveness in clinical practice were included. Classroom learning and patient use of handheld computers were excluded. Quality was assessed using the Assessment of Multiple Systematic Reviews (AMSTAR) tool. A previously published conceptual framework was used as the basis for dual data extraction. Reported outcomes were summarized according to the primary function of the handheld computer. Five systematic reviews met the inclusion and quality criteria. Together, they reviewed 138 unique primary studies. Most reviewed descriptive intervention studies, where physicians, pharmacists, or medical students used personal digital assistants. Effectiveness was demonstrated across four distinct functions of handheld computers: patient documentation, patient care, information seeking, and professional work patterns. Within each of these functions, a range of positive outcomes were reported using both objective and self-report measures. The use of handheld computers improved patient documentation through more complete recording, fewer documentation errors, and increased efficiency. Handheld computers provided easy access to clinical decision support systems and patient management systems, which improved decision making for patient care. Handheld computers saved time and gave earlier access to new information. There were also reports that handheld computers enhanced work patterns and efficiency. This scoping review summarizes the secondary evidence for effectiveness of handheld computers and mhealth. It provides a snapshot of effective use by health care professionals across four key functions. We identified evidence to suggest that handheld computers provide easy and timely access to information and enable accurate and complete documentation. Further, they can give health care professionals instant access to evidence-based decision support and patient management systems to improve clinical decision making. Finally, there is evidence that handheld computers allow health professionals to be more efficient in their work practices. It is anticipated that this evidence will guide clinicians and managers in implementing handheld computers in clinical practice and in designing future research.
Banks, Victoria A; Stanton, Neville A; Harvey, Catherine
2014-01-01
Although task analysis of pedestrian detection can provide us with useful insights into how a driver may behave in emergency situations, the cognitive elements of driver decision-making are less well understood. To assist in the design of future Advanced Driver Assistance Systems, such as Autonomous Emergency Brake systems, it is essential that the cognitive elements of the driving task are better understood. This paper uses verbal protocol analysis in an exploratory fashion to uncover the thought processes underlying behavioural outcomes represented by hard data collected using the Southampton University Driving Simulator.
13 CFR 134.409 - Decision on appeal.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Decision on appeal. 134.409 Section 134.409 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION RULES OF PROCEDURE GOVERNING... § 134.409 Decision on appeal. (a) A decision of the Administrative Law Judge under this subpart is the...
Automated Detection of Events of Scientific Interest
NASA Technical Reports Server (NTRS)
James, Mark
2007-01-01
A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.
Muratov, Eugene; Lewis, Margaret; Fourches, Denis; Tropsha, Alexander; Cox, Wendy C
2017-04-01
Objective. To develop predictive computational models forecasting the academic performance of students in the didactic-rich portion of a doctor of pharmacy (PharmD) curriculum as admission-assisting tools. Methods. All PharmD candidates over three admission cycles were divided into two groups: those who completed the PharmD program with a GPA ≥ 3; and the remaining candidates. Random Forest machine learning technique was used to develop a binary classification model based on 11 pre-admission parameters. Results. Robust and externally predictive models were developed that had particularly high overall accuracy of 77% for candidates with high or low academic performance. These multivariate models were highly accurate in predicting these groups to those obtained using undergraduate GPA and composite PCAT scores only. Conclusion. The models developed in this study can be used to improve the admission process as preliminary filters and thus quickly identify candidates who are likely to be successful in the PharmD curriculum.
Emerencia, Ando C; Boonstra, Nynke; Wunderink, Lex; de Jonge, Peter; Sytema, Sjoerd
2013-01-01
Background Mental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes. Objective This study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders. Methods The study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation. Results In all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions on perceived involvement in medical decision making (COMRADE satisfaction with communication: F1,68=0.422, P=.52; COMRADE confidence in decision: F1,67=0.086, P=.77). In addition, results of the process evaluation suggest that the intervention did not optimally fit in with routine practice of the participating teams. Conclusions The development of electronic decision aids to facilitate shared medical decision making is encouraged and many people with a psychotic disorder can work with them. This holds for both first-episode patients and long-term care patients, although the latter group might need more assistance. However, results of this paper could not support the assumption that the use of electronic decision aids increases patient involvement in medical decision making. This may be because of weak implementation of the study protocol and a low response rate. Trial Registration Dutch Trial Register (NTR) trial number: 10340; http://www.trialregister.nl/trialreg/admin/rctsearch.asp?Term=10340 (Archived by WebCite at http://www.webcitation.org/6Jj5umAeS). PMID:24100091
NASA Technical Reports Server (NTRS)
2003-01-01
With assistance from NASA s Marshall Space Flight Center, a new breed of ITS for technical training and complex problem-solving has hit the market to provide students and trainees with the decision-making skills necessary to succeed to the next level. The Task Tutor Toolkit (T3), developed by Stottler Henke Associates, Inc., of San Mateo, California, is a generic tutoring system shell and scenario authoring tool that emulates expert instructors and lowers the cost and difficulty of creating scenario-based ITS for technical training. The functionality of Stottler Henke Associates T3 far exceeds that of traditional computer-based training systems, which test factual recall and narrow skills by prompting students to answer multiple-choice or fill-inthe- blank questions. The T3, on the contrary, lets students assess situations, generate solutions, make decisions, and carry out actions in realistically complex scenarios.At the beginning of each scenario, the T3 tutoring system presents a briefing that describes the situation and the goals the students should pursue. Each scenario contains a solution template that specifies a partially-ordered sequence of action patterns that match correct sequences of student actions. During each scenario, the built-in simulator notifies the tutoring system of each student action. The T3 uses this information to evaluate the student action by comparing it with the scenario s solution template and with error rules that detect incorrect actions.
Bell, L T O; Gandhi, S
2018-06-01
To directly compare the accuracy and speed of analysis of two commercially available computer-assisted detection (CAD) programs in detecting colorectal polyps. In this retrospective single-centre study, patients who had colorectal polyps identified on computed tomography colonography (CTC) and subsequent lower gastrointestinal endoscopy, were analysed using two commercially available CAD programs (CAD1 and CAD2). Results were compared against endoscopy to ascertain sensitivity and positive predictive value (PPV) for colorectal polyps. Time taken for CAD analysis was also calculated. CAD1 demonstrated a sensitivity of 89.8%, PPV of 17.6% and mean analysis time of 125.8 seconds. CAD2 demonstrated a sensitivity of 75.5%, PPV of 44.0% and mean analysis time of 84.6 seconds. The sensitivity and PPV for colorectal polyps and CAD analysis times can vary widely between current commercially available CAD programs. There is still room for improvement. Generally, there is a trade-off between sensitivity and PPV, and so further developments should aim to optimise both. Information on these factors should be made routinely available, so that an informed choice on their use can be made. This information could also potentially influence the radiologist's use of CAD results. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Azadmanjir, Zahra; Safdari, Reza; Ghazisaeedi, Marjan; Mokhtaran, Mehrshad; Kameli, Mohammad Esmail
2017-06-01
Accurate coded data in the healthcare are critical. Computer-Assisted Coding (CAC) is an effective tool to improve clinical coding in particular when a new classification will be developed and implemented. But determine the appropriate method for development need to consider the specifications of existing CAC systems, requirements for each type, our infrastructure and also, the classification scheme. The aim of the study was the development of a decision model for determining accurate code of each medical intervention in Iranian Classification of Health Interventions (IRCHI) that can be implemented as a suitable CAC system. first, a sample of existing CAC systems was reviewed. Then feasibility of each one of CAC types was examined with regard to their prerequisites for their implementation. The next step, proper model was proposed according to the structure of the classification scheme and was implemented as an interactive system. There is a significant relationship between the level of assistance of a CAC system and integration of it with electronic medical documents. Implementation of fully automated CAC systems is impossible due to immature development of electronic medical record and problems in using language for medical documenting. So, a model was proposed to develop semi-automated CAC system based on hierarchical relationships between entities in the classification scheme and also the logic of decision making to specify the characters of code step by step through a web-based interactive user interface for CAC. It was composed of three phases to select Target, Action and Means respectively for an intervention. The proposed model was suitable the current status of clinical documentation and coding in Iran and also, the structure of new classification scheme. Our results show it was practical. However, the model needs to be evaluated in the next stage of the research.
Enterprise digital assistants: the progression of wireless clinical computing.
Bergeron, Bryan P
2002-01-01
By virtue of increasingly pervasive wireless connectivity, the proliferation of wireless handheld devices in clinical care is rapidly transforming the concept of the personal digital assistant (PDA) to the enterprise digital assistant (EDA). Wireless handheld devices are becoming extensions of the central hospital information system, in which it's understood that the health care enterprise, not the clinician carrying the information-dispensing device, owns the data. The practical implication for clinicians is that, despite the potential long-term benefits of seamless, just-in-time clinical data access, this paradigm shift portends decreased efficiency in the short term, as clinicians duplicate clinical data collection on private devices. Assuming eventual clinician acceptance, EDAs can form the basis of a national real-time clinical data acquisition system that ensures uniform prescribing, decision support, and diagnosis, and the means for tracking unusual disease presentation patterns that could be indicative of bioterrorism or natural disease outbreaks.
A decision tool for selecting trench cap designs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paige, G.B.; Stone, J.J.; Lane, L.J.
1995-12-31
A computer based prototype decision support system (PDSS) is being developed to assist the risk manager in selecting an appropriate trench cap design for waste disposal sites. The selection of the {open_quote}best{close_quote} design among feasible alternatives requires consideration of multiple and often conflicting objectives. The methodology used in the selection process consists of: selecting and parameterizing decision variables using data, simulation models, or expert opinion; selecting feasible trench cap design alternatives; ordering the decision variables and ranking the design alternatives. The decision model is based on multi-objective decision theory and uses a unique approach to order the decision variables andmore » rank the design alternatives. Trench cap designs are evaluated based on federal regulations, hydrologic performance, cover stability and cost. Four trench cap designs, which were monitored for a four year period at Hill Air Force Base in Utah, are used to demonstrate the application of the PDSS and evaluate the results of the decision model. The results of the PDSS, using both data and simulations, illustrate the relative advantages of each of the cap designs and which cap is the {open_quotes}best{close_quotes} alternative for a given set of criteria and a particular importance order of those decision criteria.« less
Fusing Symbolic and Numerical Diagnostic Computations
NASA Technical Reports Server (NTRS)
James, Mark
2007-01-01
X-2000 Anomaly Detection Language denotes a developmental computing language, and the software that establishes and utilizes the language, for fusing two diagnostic computer programs, one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for realtime detection of events (e.g., failures) in a spacecraft, aircraft, or other complex engineering system. The numerical analysis method is performed by beacon-based exception analysis for multi-missions (BEAMs), which has been discussed in several previous NASA Tech Briefs articles. The symbolic analysis method is, more specifically, an artificial-intelligence method of the knowledge-based, inference engine type, and its implementation is exemplified by the Spacecraft Health Inference Engine (SHINE) software. The goal in developing the capability to fuse numerical and symbolic diagnostic components is to increase the depth of analysis beyond that previously attainable, thereby increasing the degree of confidence in the computed results. In practical terms, the sought improvement is to enable detection of all or most events, with no or few false alarms.
Development of Instrumentation for Boundary Layer Transition Detection
1991-01-01
assistance of Maj. Aaron Byerley were largely responsible for my decision to stay on. 4t Contents Abstract Acknowledgements Nomenclature Chapter 1...The use of shr sensitive liquid crystals in aerodynamic measurements has been a mor wPu imovation. Two different prcesses can be employed to...transition location. The steady-state heat transfer technique is unsuited for use on complex geometries, may be time consuming , and has an element of
Influence of Computer-Aided Detection on Performance of Screening Mammography
Fenton, Joshua J.; Taplin, Stephen H.; Carney, Patricia A.; Abraham, Linn; Sickles, Edward A.; D'Orsi, Carl; Berns, Eric A.; Cutter, Gary; Hendrick, R. Edward; Barlow, William E.; Elmore, Joann G.
2011-01-01
Background Computer-aided detection identifies suspicious findings on mammograms to assist radiologists. Since the Food and Drug Administration approved the technology in 1998, it has been disseminated into practice, but its effect on the accuracy of interpretation is unclear. Methods We determined the association between the use of computer-aided detection at mammography facilities and the performance of screening mammography from 1998 through 2002 at 43 facilities in three states. We had complete data for 222,135 women (a total of 429,345 mammograms), including 2351 women who received a diagnosis of breast cancer within 1 year after screening. We calculated the specificity, sensitivity, and positive predictive value of screening mammography with and without computer-aided detection, as well as the rates of biopsy and breast-cancer detection and the overall accuracy, measured as the area under the receiver-operating-characteristic (ROC) curve. Results Seven facilities (16%) implemented computer-aided detection during the study period. Diagnostic specificity decreased from 90.2% before implementation to 87.2% after implementation (P<0.001), the positive predictive value decreased from 4.1% to 3.2% (P = 0.01), and the rate of biopsy increased by 19.7% (P<0.001). The increase in sensitivity from 80.4% before implementation of computer-aided detection to 84.0% after implementation was not significant (P = 0.32). The change in the cancer-detection rate (including invasive breast cancers and ductal carcinomas in situ) was not significant (4.15 cases per 1000 screening mammograms before implementation and 4.20 cases after implementation, P = 0.90). Analyses of data from all 43 facilities showed that the use of computer-aided detection was associated with significantly lower overall accuracy than was nonuse (area under the ROC curve, 0.871 vs. 0.919; P = 0.005). Conclusions The use of computer-aided detection is associated with reduced accuracy of interpretation of screening mammograms. The increased rate of biopsy with the use of computer-aided detection is not clearly associated with improved detection of invasive breast cancer. PMID:17409321
Hoff, Rodrigo Barcellos; Pizzolato, Tânia Mara; Peralba, Maria do Carmo Ruaro; Díaz-Cruz, M Silvia; Barceló, Damià
2015-03-01
Sulfonamides are widely used in human and veterinary medicine. The presence of sulfonamides residues in food is an issue of great concern. Throughout the present work, a method for the targeted analysis of 16 sulfonamides and metabolites residue in liver of several species has been developed and validated. Extraction and clean-up has been statistically optimized using central composite design experiments. Two extraction methods have been developed, validated and compared: i) pressurized liquid extraction, in which samples were defatted with hexane and subsequently extracted with acetonitrile and ii) ultrasound-assisted extraction with acetonitrile and further liquid-liquid extraction with hexane. Extracts have been analyzed by liquid chromatography-quadrupole linear ion trap-tandem mass spectrometry. Validation procedure has been based on the Commission Decision 2002/657/EC and included the assessment of parameters such as decision limit (CCα), detection capability (CCβ), sensitivity, selectivity, accuracy and precision. Method׳s performance has been satisfactory, with CCα values within the range of 111.2-161.4 µg kg(-1), limits of detection of 10 µg kg(-1) and accuracy values around 100% for all compounds. Copyright © 2014 Elsevier B.V. All rights reserved.
13 CFR 134.715 - Can a Judge reconsider his decision?
Code of Federal Regulations, 2010 CFR
2010-01-01
... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Can a Judge reconsider his decision? 134.715 Section 134.715 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION RULES OF....715 Can a Judge reconsider his decision? (a) The Judge may reconsider an appeal decision within 20...
PCA method for automated detection of mispronounced words
NASA Astrophysics Data System (ADS)
Ge, Zhenhao; Sharma, Sudhendu R.; Smith, Mark J. T.
2011-06-01
This paper presents a method for detecting mispronunciations with the aim of improving Computer Assisted Language Learning (CALL) tools used by foreign language learners. The algorithm is based on Principle Component Analysis (PCA). It is hierarchical with each successive step refining the estimate to classify the test word as being either mispronounced or correct. Preprocessing before detection, like normalization and time-scale modification, is implemented to guarantee uniformity of the feature vectors input to the detection system. The performance using various features including spectrograms and Mel-Frequency Cepstral Coefficients (MFCCs) are compared and evaluated. Best results were obtained using MFCCs, achieving up to 99% accuracy in word verification and 93% in native/non-native classification. Compared with Hidden Markov Models (HMMs) which are used pervasively in recognition application, this particular approach is computational efficient and effective when training data is limited.
A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks
Zhang, Shukui; Chen, Hao; Zhu, Qiaoming
2014-01-01
The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic. PMID:25136690
NASA Astrophysics Data System (ADS)
Kojima, Yohei; Takeda, Kazuaki; Adachi, Fumiyuki
Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can provide better downlink bit error rate (BER) performance of direct sequence code division multiple access (DS-CDMA) than the conventional rake combining in a frequency-selective fading channel. FDE requires accurate channel estimation. In this paper, we propose a new 2-step maximum likelihood channel estimation (MLCE) for DS-CDMA with FDE in a very slow frequency-selective fading environment. The 1st step uses the conventional pilot-assisted MMSE-CE and the 2nd step carries out the MLCE using decision feedback from the 1st step. The BER performance improvement achieved by 2-step MLCE over pilot assisted MMSE-CE is confirmed by computer simulation.
Decaestecker, C; Salmon, I; Camby, I; Dewitte, O; Pasteels, J L; Brotchi, J; Van Ham, P; Kiss, R
1995-05-01
The present work investigates whether computer-assisted techniques can contribute any significant information to the characterization of astrocytic tumor aggressiveness. Two complementary computer-assisted methods were used. The first method made use of the digital image analysis of Feulgen-stained nuclei, making it possible to compute 15 morphonuclear and 8 nuclear DNA content-related (ploidy level) parameters. The second method enabled the most discriminatory parameters to be determined. This second method is the Decision Tree technique, which forms part of the Supervised Learning Algorithms. These two techniques were applied to a series of 250 supratentorial astrocytic tumors of the adult. This series included 39 low-grade (astrocytomas, AST) and 211 high-grade (47 anaplastic astrocytomas, ANA, and 164 glioblastomas, GBM) astrocytic tumors. The results show that some AST, ANA and GBM did not fit within simple logical rules. These "complex" cases were labeled NC-AST, NC-ANA and NC-GBM because they were "non-classical" (NC) with respect to their cytological features. An analysis of survival data revealed that the patients with NC-GBM had the same survival period as patients with GBM. In sharp contrast, patients with ANA survived significantly longer than patients with NC-ANA. In fact, the patients with ANA had the same survival period as patients who died from AST, while the patients with NC-ANA had a survival period similar to those with GBM. All these data show that the computer-assisted techniques used in this study can actually provide the pathologist with significant information on the characterization of astrocytic tumor aggressiveness.
Evaluation of ilmenite serpentine concrete and ordinary concrete as nuclear reactor shielding
NASA Astrophysics Data System (ADS)
Abulfaraj, Waleed H.; Kamal, Salah M.
1994-07-01
The present study involves adapting a formal decision methodology to the selection of alternative nuclear reactor concretes shielding. Multiattribute utility theory is selected to accommodate decision makers' preferences. Multiattribute utility theory (MAU) is here employed to evaluate two appropriate nuclear reactor shielding concretes in terms of effectiveness to determine the optimal choice in order to meet the radiation protection regulations. These concretes are Ordinary concrete (O.C.) and Ilmenite Serpentile concrete (I.S.C.). These are normal weight concrete and heavy heat resistive concrete, respectively. The effectiveness objective of the nuclear reactor shielding is defined and structured into definite attributes and subattributes to evaluate the best alternative. Factors affecting the decision are dose received by reactor's workers, the material properties as well as cost of concrete shield. A computer program is employed to assist in performing utility analysis. Based upon data, the result shows the superiority of Ordinary concrete over Ilmenite Serpentine concrete.
Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees
NASA Astrophysics Data System (ADS)
Khryashchev, V. V.; Lebedev, A. A.; Priorov, A. L.
2017-05-01
Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.
Histopathological Image Analysis: A Review
Gurcan, Metin N.; Boucheron, Laura; Can, Ali; Madabhushi, Anant; Rajpoot, Nasir; Yener, Bulent
2010-01-01
Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement to the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe. PMID:20671804
2014-12-01
Hypertension is one of the most common co-morbidities associated with DM and substantially contributes to the macrovascular disease that occurs in...After Numera terminated the contract to provide glucometer download support Estenda activated the patient portal , Diabetes Mellitus Everywhere...several patients. Problem areas include having to download JAVA with first upload and accessing the DME portal . d. PO has downloaded glucose
Perceptual learning effect on decision and confidence thresholds.
Solovey, Guillermo; Shalom, Diego; Pérez-Schuster, Verónica; Sigman, Mariano
2016-10-01
Practice can enhance of perceptual sensitivity, a well-known phenomenon called perceptual learning. However, the effect of practice on subjective perception has received little attention. We approach this problem from a visual psychophysics and computational modeling perspective. In a sequence of visual search experiments, subjects significantly increased the ability to detect a "trained target". Before and after training, subjects performed two psychophysical protocols that parametrically vary the visibility of the "trained target": an attentional blink and a visual masking task. We found that confidence increased after learning only in the attentional blink task. Despite large differences in some observables and task settings, we identify common mechanisms for decision-making and confidence. Specifically, our behavioral results and computational model suggest that perceptual ability is independent of processing time, indicating that changes in early cortical representations are effective, and learning changes decision criteria to convey choice and confidence. Copyright © 2016 Elsevier Inc. All rights reserved.
Big data, smart homes and ambient assisted living.
Vimarlund, V; Wass, S
2014-08-15
To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data. A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014. The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc. The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today's services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability.
Lopez, Ramón Guisado; Polo, Isabel Ramirez; Berral, Jose Eduardo Arjona; Fernandez, Julia Guisado; Castelo-Branco, Camil
2015-04-01
To design software to assist health care providers with contraceptive counselling. The Model-View-Controller software architecture pattern was used. Decision logic was incorporated to automatically compute the safety category of each contraceptive option. Decisions are made according to the specific characteristics or known medical conditions of each potential contraception user. The software is an app designed for the iOS and Android platforms and is available in four languages. iContraception(®) facilitates presentation of visual data on medical eligibility criteria for contraceptive treatments. The use of this software was evaluated by a sample of 54 health care providers. The general satisfaction with the use of the app was over 8 on a 0-10 visual analogue scale in 96.3% of cases. iContraception provides easy access to medical eligibility criteria of contraceptive options and may help with contraceptive counselling. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Motivation alters response bias and neural activation patterns in a perceptual decision-making task.
Reckless, G E; Bolstad, I; Nakstad, P H; Andreassen, O A; Jensen, J
2013-05-15
Motivation has been demonstrated to affect individuals' response strategies in economic decision-making, however, little is known about how motivation influences perceptual decision-making behavior or its related neural activity. Given the important role motivation plays in shaping our behavior, a better understanding of this relationship is needed. A block-design, continuous performance, perceptual decision-making task where participants were asked to detect a picture of an animal among distractors was used during functional magnetic resonance imaging (fMRI). The effect of positive and negative motivation on sustained activity within regions of the brain thought to underlie decision-making was examined by altering the monetary contingency associated with the task. In addition, signal detection theory was used to investigate the effect of motivation on detection sensitivity, response bias and response time. While both positive and negative motivation resulted in increased sustained activation in the ventral striatum, fusiform gyrus, left dorsolateral prefrontal cortex (DLPFC) and ventromedial prefrontal cortex, only negative motivation resulted in the adoption of a more liberal, closer to optimal response bias. This shift toward a liberal response bias correlated with increased activation in the left DLPFC, but did not result in improved task performance. The present findings suggest that motivation alters aspects of the way perceptual decisions are made. Further, this altered response behavior is reflected in a change in left DLPFC activation, a region involved in the computation of perceptual decisions. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.
Satisfaction of Search in Chest Radiography 2015.
Berbaum, Kevin S; Krupinski, Elizabeth A; Schartz, Kevin M; Caldwell, Robert T; Madsen, Mark T; Hur, Seung; Laroia, Archana T; Thompson, Brad H; Mullan, Brian F; Franken, Edmund A
2015-11-01
Two decades have passed since the publication of laboratory studies of satisfaction of search (SOS) in chest radiography. Those studies were performed using film. The current investigation tests for SOS effects in computed radiography of the chest. Sixty-four chest computed radiographs half demonstrating various "test" abnormalities were read twice by 20 radiologists, once with and once without the addition of a simulated pulmonary nodule. Receiver-operating characteristic detection accuracy and decision thresholds were analyzed to study the effects of adding the nodule on detecting the test abnormalities. Results of previous studies were reanalyzed using similar modern techniques. In the present study, adding nodules did not influence detection accuracy for the other abnormalities (P = .93), but did induce a reluctance to report them (P < .001). Adding nodules did not affect inspection time (P = .58) so the reluctance to report was not associated with reduced search. Reanalysis revealed a similar decision threshold shift that had not been recognized in the early studies of SOS in chest radiography (P < .01) in addition to reduced detection accuracy (P < .01). The nature of SOS in chest radiography has changed, but it is not clear why. SOS may be changing as a function of changes in radiology education and practice. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.
The ALICE System: A Workbench for Learning and Using Language.
ERIC Educational Resources Information Center
Levin, Lori; And Others
1991-01-01
ALICE, a multimedia framework for intelligent computer-assisted language instruction (ICALI) at Carnegie Mellon University (PA), consists of a set of tools for building a number of different types of ICALI programs in any language. Its Natural Language Processing tools for syntactic error detection, morphological analysis, and generation of…
Decaestecker, C; van Velthoven, R; Petein, M; Janssen, T; Salmon, I; Pasteels, J L; van Ham, P; Schulman, C; Kiss, R
1996-03-01
The aggressiveness of human bladder tumours can be assessed by means of various classification systems, including the one proposed by the World Health Organization (WHO). According to the WHO classification, three levels of malignancy are identified as grades I (low), II (intermediate), and III (high). This classification system operates satisfactorily for two of the three grades in forecasting clinical progression, most grade I tumours being associated with good prognoses and most grade III with bad. In contrast, the grade II group is very heterogeneous in terms of their clinical behaviour. The present study used two computer-assisted methods to investigate whether it is possible to sub-classify grade II tumours: computer-assisted microscope analysis (image cytometry) of Feulgen-stained nuclei and the Decision Tree Technique. This latter technique belongs to the Supervised Learning Algorithm and enables an objective assessment to be made of the diagnostic value associated with a given parameter. The combined use of these two methods in a series of 292 superficial transitional cell carcinomas shows that it is possible to identify one subgroup of grade II tumours which behave clinically like grade I tumours and a second subgroup which behaves clinically like grade III tumours. Of the nine ploidy-related parameters computed by means of image cytometry [the DNA index (DI), DNA histogram type (DHT), and the percentages of diploid, hyperdiploid, triploid, hypertriploid, tetraploid, hypertetraploid, and polyploid cell nuclei], it was the percentage of hyperdiploid and hypertetraploid cell nuclei which enabled identification, rather than conventional parameters such as the DI or the DHT.
Prospective Architectures for Onboard vs Cloud-Based Decision Making for Unmanned Aerial Systems
NASA Technical Reports Server (NTRS)
Sankararaman, Shankar; Teubert, Christopher
2017-01-01
This paper investigates propsective architectures for decision-making in unmanned aerial systems. When these unmanned vehicles operate in urban environments, there are several sources of uncertainty that affect their behavior, and decision-making algorithms need to be robust to account for these different sources of uncertainty. It is important to account for several risk-factors that affect the flight of these unmanned systems, and facilitate decision-making by taking into consideration these various risk-factors. In addition, there are several technical challenges related to autonomous flight of unmanned aerial systems; these challenges include sensing, obstacle detection, path planning and navigation, trajectory generation and selection, etc. Many of these activities require significant computational power and in many situations, all of these activities need to be performed in real-time. In order to efficiently integrate these activities, it is important to develop a systematic architecture that can facilitate real-time decision-making. Four prospective architectures are discussed in this paper; on one end of the spectrum, the first architecture considers all activities/computations being performed onboard the vehicle whereas on the other end of the spectrum, the fourth and final architecture considers all activities/computations being performed in the cloud, using a new service known as Prognostics as a Service that is being developed at NASA Ames Research Center. The four different architectures are compared, their advantages and disadvantages are explained and conclusions are presented.
A Mobile Decision Aid for Determining Detection Probabilities for Acoustic Targets
2002-08-01
propagation mobile application . Personal Computer Memory Card International Association, an organization of some 500 companies that has developed a...SENSOR: lHuman and possible outputs, it was felt that for a mobile application , the interface and number of output parameters should be kept simple...value could be computed on the server and transmitted back to the mobile application for display. FUTURE CAPABILITIES 2-D/3-D Displays The full ABFA
Ubiquitous computing technology for just-in-time motivation of behavior change.
Intille, Stephen S
2004-01-01
This paper describes a vision of health care where "just-in-time" user interfaces are used to transform people from passive to active consumers of health care. Systems that use computational pattern recognition to detect points of decision, behavior, or consequences automatically can present motivational messages to encourage healthy behavior at just the right time. Further, new ubiquitous computing and mobile computing devices permit information to be conveyed to users at just the right place. In combination, computer systems that present messages at the right time and place can be developed to motivate physical activity and healthy eating. Computational sensing technologies can also be used to measure the impact of the motivational technology on behavior.
NASA Astrophysics Data System (ADS)
De Lorenzo, Danilo; De Momi, Elena; Beretta, Elisa; Cerveri, Pietro; Perona, Franco; Ferrigno, Giancarlo
2009-02-01
Computer Assisted Orthopaedic Surgery (CAOS) systems improve the results and the standardization of surgical interventions. Anatomical landmarks and bone surface detection is straightforward to either register the surgical space with the pre-operative imaging space and to compute biomechanical parameters for prosthesis alignment. Surface points acquisition increases the intervention invasiveness and can be influenced by the soft tissue layer interposition (7-15mm localization errors). This study is aimed at evaluating the accuracy of a custom-made A-mode ultrasound (US) system for non invasive detection of anatomical landmarks and surfaces. A-mode solutions eliminate the necessity of US images segmentation, offers real-time signal processing and requires less invasive equipment. The system consists in a single transducer US probe optically tracked, a pulser/receiver and an FPGA-based board, which is responsible for logic control command generation and for real-time signal processing and three custom-made board (signal acquisition, blanking and synchronization). We propose a new calibration method of the US system. The experimental validation was then performed measuring the length of known-shape polymethylmethacrylate boxes filled with pure water and acquiring bone surface points on a bovine bone phantom covered with soft-tissue mimicking materials. Measurement errors were computed through MR and CT images acquisitions of the phantom. Points acquisition on bone surface with the US system demonstrated lower errors (1.2mm) than standard pointer acquisition (4.2mm).
13 CFR 130.430 - Application decisions.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 13 Business Credit and Assistance 1 2011-01-01 2011-01-01 false Application decisions. 130.430 Section 130.430 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION SMALL BUSINESS DEVELOPMENT CENTERS § 130.430 Application decisions. (a) The AA/SBDCs may approve, conditionally approve, or reject...
29 CFR 2509.96-1 - Interpretive bulletin relating to participant investment education.
Code of Federal Regulations, 2010 CFR
2010-07-01
...., regarding general investment principles and strategies, to assist them in making investment decisions. 29..., whose investment decisions will directly affect their income at retirement, with information designed to assist them in making investment and retirement-related decisions appropriate to their particular...
Infrared imaging based hyperventilation monitoring through respiration rate estimation
NASA Astrophysics Data System (ADS)
Basu, Anushree; Routray, Aurobinda; Mukherjee, Rashmi; Shit, Suprosanna
2016-07-01
A change in the skin temperature is used as an indicator of physical illness which can be detected through infrared thermography. Thermograms or thermal images can be used as an effective diagnostic tool for monitoring and diagnosis of various diseases. This paper describes an infrared thermography based approach for detecting hyperventilation caused due to stress and anxiety in human beings by computing their respiration rates. The work employs computer vision techniques for tracking the region of interest from thermal video to compute the breath rate. Experiments have been performed on 30 subjects. Corner feature extraction using Minimum Eigenvalue (Shi-Tomasi) algorithm and registration using Kanade Lucas-Tomasi algorithm has been used here. Thermal signature around the extracted region is detected and subsequently filtered through a band pass filter to compute the respiration profile of an individual. If the respiration profile shows unusual pattern and exceeds the threshold we conclude that the person is stressed and tending to hyperventilate. Results obtained are compared with standard contact based methods which have shown significant correlations. It is envisaged that the thermal image based approach not only will help in detecting hyperventilation but can assist in regular stress monitoring as it is non-invasive method.
Sarikaya, Duygu; Corso, Jason J; Guru, Khurshid A
2017-07-01
Video understanding of robot-assisted surgery (RAS) videos is an active research area. Modeling the gestures and skill level of surgeons presents an interesting problem. The insights drawn may be applied in effective skill acquisition, objective skill assessment, real-time feedback, and human-robot collaborative surgeries. We propose a solution to the tool detection and localization open problem in RAS video understanding, using a strictly computer vision approach and the recent advances of deep learning. We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos. To the best of our knowledge, this approach will be the first to incorporate deep neural networks for tool detection and localization in RAS videos. Our architecture applies a region proposal network (RPN) and a multimodal two stream convolutional network for object detection to jointly predict objectness and localization on a fusion of image and temporal motion cues. Our results with an average precision of 91% and a mean computation time of 0.1 s per test frame detection indicate that our study is superior to conventionally used methods for medical imaging while also emphasizing the benefits of using RPN for precision and efficiency. We also introduce a new data set, ATLAS Dione, for RAS video understanding. Our data set provides video data of ten surgeons from Roswell Park Cancer Institute, Buffalo, NY, USA, performing six different surgical tasks on the daVinci Surgical System (dVSS) with annotations of robotic tools per frame.
Decision support methods for the detection of adverse events in post-marketing data.
Hauben, M; Bate, A
2009-04-01
Spontaneous reporting is a crucial component of post-marketing drug safety surveillance despite its significant limitations. The size and complexity of some spontaneous reporting system databases represent a challenge for drug safety professionals who traditionally have relied heavily on the scientific and clinical acumen of the prepared mind. Computer algorithms that calculate statistical measures of reporting frequency for huge numbers of drug-event combinations are increasingly used to support pharamcovigilance analysts screening large spontaneous reporting system databases. After an overview of pharmacovigilance and spontaneous reporting systems, we discuss the theory and application of contemporary computer algorithms in regular use, those under development, and the practical considerations involved in the implementation of computer algorithms within a comprehensive and holistic drug safety signal detection program.
Bass, Sarah Bauerle; Gordon, Thomas F.; Ruzek, Sheryl Burt; Wolak, Caitlin; Ruggieri, Dominique; Mora, Gabriella; Rovito, Michael J.; Britto, Johnson; Parameswaran, Lalitha; Abedin, Zainab; Ward, Stephanie; Paranjape, Anuradha; Lin, Karen; Meyer, Brian; Pitts, Khaliah
2017-01-01
African Americans have higher colorectal cancer (CRC) mortality than White Americans and yet have lower rates of CRC screening. Increased screening aids in early detection and higher survival rates. Coupled with low literacy rates, the burden of CRC morbidity and mortality is exacerbated in this population, making it important to develop culturally and literacy appropriate aids to help low-literacy African Americans make informed decisions about CRC screening. This article outlines the development of a low-literacy computer touch-screen colonoscopy decision aid using an innovative marketing method called perceptual mapping and message vector modeling. This method was used to mathematically model key messages for the decision aid, which were then used to modify an existing CRC screening tutorial with different messages. The final tutorial was delivered through computer touch-screen technology to increase access and ease of use for participants. Testing showed users were not only more comfortable with the touch-screen technology but were also significantly more willing to have a colonoscopy compared with a “usual care group.” Results confirm the importance of including participants in planning and that the use of these innovative mapping and message design methods can lead to significant CRC screening attitude change. PMID:23132838
2013-01-01
Background Handheld computers and mobile devices provide instant access to vast amounts and types of useful information for health care professionals. Their reduced size and increased processing speed has led to rapid adoption in health care. Thus, it is important to identify whether handheld computers are actually effective in clinical practice. Objective A scoping review of systematic reviews was designed to provide a quick overview of the documented evidence of effectiveness for health care professionals using handheld computers in their clinical work. Methods A detailed search, sensitive for systematic reviews was applied for Cochrane, Medline, EMBASE, PsycINFO, Allied and Complementary Medicine Database (AMED), Global Health, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases. All outcomes that demonstrated effectiveness in clinical practice were included. Classroom learning and patient use of handheld computers were excluded. Quality was assessed using the Assessment of Multiple Systematic Reviews (AMSTAR) tool. A previously published conceptual framework was used as the basis for dual data extraction. Reported outcomes were summarized according to the primary function of the handheld computer. Results Five systematic reviews met the inclusion and quality criteria. Together, they reviewed 138 unique primary studies. Most reviewed descriptive intervention studies, where physicians, pharmacists, or medical students used personal digital assistants. Effectiveness was demonstrated across four distinct functions of handheld computers: patient documentation, patient care, information seeking, and professional work patterns. Within each of these functions, a range of positive outcomes were reported using both objective and self-report measures. The use of handheld computers improved patient documentation through more complete recording, fewer documentation errors, and increased efficiency. Handheld computers provided easy access to clinical decision support systems and patient management systems, which improved decision making for patient care. Handheld computers saved time and gave earlier access to new information. There were also reports that handheld computers enhanced work patterns and efficiency. Conclusions This scoping review summarizes the secondary evidence for effectiveness of handheld computers and mhealth. It provides a snapshot of effective use by health care professionals across four key functions. We identified evidence to suggest that handheld computers provide easy and timely access to information and enable accurate and complete documentation. Further, they can give health care professionals instant access to evidence-based decision support and patient management systems to improve clinical decision making. Finally, there is evidence that handheld computers allow health professionals to be more efficient in their work practices. It is anticipated that this evidence will guide clinicians and managers in implementing handheld computers in clinical practice and in designing future research. PMID:24165786
Federal Register 2010, 2011, 2012, 2013, 2014
2010-11-15
... DEPARTMENT OF ENERGY Office of Energy Efficiency and Renewable Energy [Case No. CW-015] Energy... November 4, 2010. Cathy Zoi, Assistant Secretary, Energy Efficiency and Renewable Energy. Decision and...)(1)(iii). The Assistant Secretary for Energy Efficiency and Renewable Energy (the Assistant Secretary...
Interactive tele-radiological segmentation systems for treatment and diagnosis.
Zimeras, S; Gortzis, L G
2012-01-01
Telehealth is the exchange of health information and the provision of health care services through electronic information and communications technology, where participants are separated by geographic, time, social and cultural barriers. The shift of telemedicine from desktop platforms to wireless and mobile technologies is likely to have a significant impact on healthcare in the future. It is therefore crucial to develop a general information exchange e-medical system to enables its users to perform online and offline medical consultations through diagnosis. During the medical diagnosis, image analysis techniques combined with doctor's opinions could be useful for final medical decisions. Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. In medical images, segmentation has traditionally been done by human experts. Even with the aid of image processing software (computer-assisted segmentation tools), manual segmentation of 2D and 3D CT images is tedious, time-consuming, and thus impractical, especially in cases where a large number of objects must be specified. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. The main purpose of this work is to analyze segmentation techniques for the definition of anatomical structures under telemedical systems.
NASA Astrophysics Data System (ADS)
Georgiou, Harris
2009-10-01
Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.
Line grouping using perceptual saliency and structure prediction for car detection in traffic scenes
NASA Astrophysics Data System (ADS)
Denasi, Sandra; Quaglia, Giorgio
1993-08-01
Autonomous and guide assisted vehicles make a heavy use of computer vision techniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. This approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.
ERIC Educational Resources Information Center
Murillo, Leo
2017-01-01
The purpose of this causal comparative study is to determine whether the assistant principal decision-making process and their years of experience influence the advanced diploma rates in high schools on Long Island, New York. The subjects for this study were 75 assistant principals in Long Island high schools during 2016. Assistant principals'…
29 CFR 1905.30 - Decision of the Assistant Secretary.
Code of Federal Regulations, 2010 CFR
2010-07-01
... UNDER THE WILLIAMS-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 Hearings § 1905.30 Decision of the... 29 Labor 5 2010-07-01 2010-07-01 false Decision of the Assistant Secretary. 1905.30 Section 1905.30 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION...
13 CFR 134.404 - Decision by Administrative Law Judge.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Decision by Administrative Law Judge. 134.404 Section 134.404 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION RULES OF... 8(a) Program § 134.404 Decision by Administrative Law Judge. Appeal proceedings brought under this...
45 CFR 99.33 - Effective date of Assistant Secretary's decision.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 45 Public Welfare 1 2010-10-01 2010-10-01 false Effective date of Assistant Secretary's decision. 99.33 Section 99.33 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION PROCEDURE FOR HEARINGS FOR THE CHILD CARE AND DEVELOPMENT FUND Posthearing Procedures, Decisions § 99.33...
Technical Assistance for States | State, Local, and Tribal Governments |
on energy efficiency and renewable energy policies and issues for state and local government decision issues for state and local government decision makers. The expert assistance is intended to support legislators, regulators, state agencies, and their staff members in making informed decisions about solar
Using computer software to improve group decision-making.
Mockler, R J; Dologite, D G
1991-08-01
This article provides a review of some of the work done in the area of knowledge-based systems for strategic planning. Since 1985, with the founding of the Center for Knowledge-based Systems for Business Management, the project has focused on developing knowledge-based systems (KBS) based on these models. In addition, the project also involves developing a variety of computer and non-computer methods and techniques for assisting both technical and non-technical managers and individuals to do decision modelling and KBS development. This paper presents a summary of one segment of the project: a description of integrative groupware useful in strategic planning. The work described here is part of an ongoing research project. As part of this project, for example, over 200 non-technical and technical business managers, most of them working full-time during the project, developed over 160 KBS prototype systems in conjunction with MBA course in strategic planning and management decision making. Based on replies to a survey of this test group, 28 per cent of the survey respondents reported their KBS were used at work, 21 per cent reportedly received promotions, pay rises or new jobs based on their KBS development work, and 12 per cent reported their work led to participation in other KBS development projects at work. All but two of the survey respondents reported that their work on the KBS development project led to a substantial increase in their job knowledge or performance.
Lumber defect detection by ultrasonics
K. A. McDonald
1978-01-01
Ultrasonics, the technology of high-frequency sound, has been developed as a viable means for locating most defects In lumber for use in digital form in decision-making computers. Ultrasonics has the potential for locating surface and internal defects in lumber of all species, green or dry, and rough sawn or surfaced.
42 CFR 430.102 - Decisions following hearing.
Code of Federal Regulations, 2010 CFR
2010-10-01
... (CONTINUED) MEDICAL ASSISTANCE PROGRAMS GRANTS TO STATES FOR MEDICAL ASSISTANCE PROGRAMS Hearings on Conformity of State Medicaid Plans and Practice to Federal Requirements § 430.102 Decisions following hearing...
Computer-Assisted Diagnosis of the Sleep Apnea-Hypopnea Syndrome: A Review
Alvarez-Estevez, Diego; Moret-Bonillo, Vicente
2015-01-01
Automatic diagnosis of the Sleep Apnea-Hypopnea Syndrome (SAHS) has become an important area of research due to the growing interest in the field of sleep medicine and the costs associated with its manual diagnosis. The increment and heterogeneity of the different techniques, however, make it somewhat difficult to adequately follow the recent developments. A literature review within the area of computer-assisted diagnosis of SAHS has been performed comprising the last 15 years of research in the field. Screening approaches, methods for the detection and classification of respiratory events, comprehensive diagnostic systems, and an outline of current commercial approaches are reviewed. An overview of the different methods is presented together with validation analysis and critical discussion of the current state of the art. PMID:26266052
Vaccine Hesitancy in Discussion Forums: Computer-Assisted Argument Mining with Topic Models.
Skeppstedt, Maria; Kerren, Andreas; Stede, Manfred
2018-01-01
Arguments used when vaccination is debated on Internet discussion forums might give us valuable insights into reasons behind vaccine hesitancy. In this study, we applied automatic topic modelling on a collection of 943 discussion posts in which vaccine was debated, and six distinct discussion topics were detected by the algorithm. When manually coding the posts ranked as most typical for these six topics, a set of semantically coherent arguments were identified for each extracted topic. This indicates that topic modelling is a useful method for automatically identifying vaccine-related discussion topics and for identifying debate posts where these topics are discussed. This functionality could facilitate manual coding of salient arguments, and thereby form an important component in a system for computer-assisted coding of vaccine-related discussions.
Assessing the activity of sarcoidosis: quantitative /sup 67/Ga-citrate imaging
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fajman, W.A.; Greenwald, L.V.; Staton, G.
1984-04-01
Three different methods of quantitating /sup 67/Ga-citrate lung images - a visual index, a computer-assisted index, and the total-lung-to-background ratio - were compared in 71 studies of patients with biopsy-proven sarcoidosis. Fifty consecutive cases were analyzed independently by two different observers using all three methods. In these studies, each index was correlated with the cell differential in the bronchoalveolar lavage fluid. The total-lung-to-background ratio proved to be the simplest to perform; correlated best with the original visual index and the percentage of lymphocytes obtained in bronchoalveolar lavage fluid. Sensitivity for detecting active disease was 84% compared with 64% and 58%more » for the visual and computer-assisted indices, respectively, with no sacrifice in specificity.« less
Developing screening services for colorectal cancer on Android smartphones.
Wu, Hui-Ching; Chang, Chiao-Jung; Lin, Chun-Che; Tsai, Ming-Chang; Chang, Che-Chia; Tseng, Ming-Hseng
2014-08-01
Colorectal cancer (CRC) is an important health problem in Western countries and also in Asia. It is the third leading cause of cancer deaths in both men and women in Taiwan. According to the well-known adenoma-to-carcinoma sequence, the majority of CRC develops from colorectal adenomatous polyps. This concept provides the rationale for screening and prevention of CRC. Removal of colorectal adenoma could reduce the mortality and incidence of CRC. Mobile phones are now playing an ever more crucial role in people's daily lives. The latest generation of smartphones is increasingly viewed as hand-held computers rather than as phones, because of their powerful on-board computing capability, capacious memories, large screens, and open operating systems that encourage development of applications (apps). If we can detect the potential CRC patients early and offer them appropriate treatments and services, this would not only promote the quality of life, but also reduce the possible serious complications and medical costs. In this study, an intelligent CRC screening app on Android™ (Google™, Mountain View, CA) smartphones has been developed based on a data mining approach using decision tree algorithms. For comparison, the stepwise backward multivariate logistic regression model and the fecal occult blood test were also used. Compared with the stepwise backward multivariate logistic regression model and the fecal occult blood test, the proposed app system not only provides an easy and efficient way to quickly detect high-risk groups of potential CRC patients, but also brings more information about CRC to customer-oriented services. We developed and implemented an app system on Android platforms for ubiquitous healthcare services for CRC screening. It can assist people in achieving early screening, diagnosis, and treatment purposes, prevent the occurrence of complications, and thus reach the goal of preventive medicine.
Musiimenta, Angella
2012-01-01
Background: Although Uganda had recorded declines in HIV infection rates around 1990’s, it is argued that HIV/AIDS risk sexual behaviour, especially among the youth, started increasing again from early 2000. School-based computer-assisted HIV interventions can provide interactive ways of improving the youth’s HIV knowledge, attitudes and skills. However, these interventions have long been reported to have limited success in improving the youth’s sexual behaviours, which is always the major aim of implementing such interventions. This could be because the commonly used health promotion theories employed by these interventions have limited application in HIV prevention. These theories tend to lack sufficient attention to contextual mediators that influence ones sexual behaviours. Moreover, literature increasingly expresses dissatisfaction with the dominant prevailing descriptive survey-type HIV/AIDS-related research. Objective and Methods: The objective of this research was to identify contextual mediators that influence the youth’s decision to adopt and maintain the HIV/AIDS preventive behaviour advocated by a computer-assisted intervention. To achieve this objective, this research employed qualitative method, which provided in-depth understanding of how different contexts interact to influence the effectiveness of HIV/AIDS interventions. The research question was: What contextual mediators are influencing the youth’s decision to adopt and maintain the HIV/AIDS preventive behaviour advocated by a computer-assisted intervention? To answer this research question, 20 youth who had previously completed the WSWM intervention when they were still in secondary schools were telephone interviewed between Sept.08 and Dec.08. The collected data was then analysed, based on grounded theory’s coding scheme. Results: Findings demonstrate that although often ignored by HIV interventionists and researchers, variety of contextual mediators influence individual uptake of HIV preventives. These include relationship characteristics, familial mediators, peer influence, gender-based social norms, economic factors and religious beliefs. Conclusion: To generate concomitant mutual efforts, rather than exclusively focusing on individual level mediators, there is an urgent need to shift to integrative approaches, which combine individual level change strategies with contextual level change approaches in the design and implementation of interventional strategies to fight against HIV/AIDS. PMID:23569636
ICCE/ICCAI 2000 Full & Short Papers (Computer-Assisted Language Learning).
ERIC Educational Resources Information Center
2000
This document contains the following full and short papers on computer-assisted language learning (CALL) from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction): (1) "A Computer-Assisted English Abstract Words Learning Environment on the Web" (Wenli Tsou and…
Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project
Benammar Elgaaied, Amel; Cascio, Donato; Bruno, Salvatore; Ciaccio, Maria Cristina; Cipolla, Marco; Fauci, Alessandro; Morgante, Rossella; Taormina, Vincenzo; Gorgi, Yousr; Marrakchi Triki, Raja; Ben Ahmed, Melika; Louzir, Hechmi; Yalaoui, Sadok; Imene, Sfar; Issaoui, Yassine; Abidi, Ahmed; Ammar, Myriam; Bedhiafi, Walid; Ben Fraj, Oussama; Bouhaha, Rym; Hamdi, Khouloud; Soumaya, Koudhi; Neili, Bilel; Asma, Gati; Lucchese, Mariano; Catanzaro, Maria; Barbara, Vincenza; Brusca, Ignazio; Fregapane, Maria; Amato, Gaetano; Friscia, Giuseppe; Neila, Trai; Turkia, Souayeh; Youssra, Haouami; Rekik, Raja; Bouokez, Hayet; Vasile Simone, Maria; Fauci, Francesco; Raso, Giuseppe
2016-01-01
Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of a CAD (Computer Aided Detection) solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%), higher Patterns Accuracy (79,3% versus 48,0% and 66,2%), and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%). PMID:27042658
NASA Astrophysics Data System (ADS)
Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou
2006-03-01
Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.
42 CFR 430.96 - Record for decision.
Code of Federal Regulations, 2010 CFR
2010-10-01
...) MEDICAL ASSISTANCE PROGRAMS GRANTS TO STATES FOR MEDICAL ASSISTANCE PROGRAMS Hearings on Conformity of State Medicaid Plans and Practice to Federal Requirements § 430.96 Record for decision. The transcript...
Computer-assisted innovations in craniofacial surgery.
Rudman, Kelli; Hoekzema, Craig; Rhee, John
2011-08-01
Reconstructive surgery for complex craniofacial defects challenges even the most experienced surgeons. Preoperative reconstructive planning requires consideration of both functional and aesthetic properties of the mandible, orbit, and midface. Technological innovations allow for computer-assisted preoperative planning, computer-aided manufacturing of patient-specific implants (PSIs), and computer-assisted intraoperative navigation. Although many case reports discuss computer-assisted preoperative planning and creation of custom implants, a general overview of computer-assisted innovations is not readily available. This article reviews innovations in computer-assisted reconstructive surgery including anatomic considerations when using PSIs, technologies available for preoperative planning, work flow and process of obtaining a PSI, and implant materials available for PSIs. A case example follows illustrating the use of this technology in the reconstruction of an orbital-frontal-temporal defect with a PSI. Computer-assisted reconstruction of complex craniofacial defects provides the reconstructive surgeon with innovative options for challenging reconstructive cases. As technology advances, applications of computer-assisted reconstruction will continue to expand. © Thieme Medical Publishers.
Automated Error Detection for Developing Grammar Proficiency of ESL Learners
ERIC Educational Resources Information Center
Feng, Hui-Hsien; Saricaoglu, Aysel; Chukharev-Hudilainen, Evgeny
2016-01-01
Thanks to natural language processing technologies, computer programs are actively being used not only for holistic scoring, but also for formative evaluation of writing. CyWrite is one such program that is under development. The program is built upon Second Language Acquisition theories and aims to assist ESL learners in higher education by…
Awareness of pharmaceutical cost-assistance programs among inner-city seniors.
Federman, Alex D; Safran, Dana Gelb; Keyhani, Salomeh; Cole, Helen; Halm, Ethan A; Siu, Albert L
2009-04-01
Lack of awareness may be a significant barrier to participation by low- and middle-income seniors in pharmaceutical cost-assistance programs. The goal of this study was to determine whether older adults' awareness of 2 major state and federal pharmaceutical cost-assistance programs was associated with the seniors' ability to access and process information about assistance programs. Data were gathered from a cross-sectional study of independently living, English- or Spanish-speaking adults aged > or =60 years. Participants were interviewed in 30 community-based settings (19 apartment complexes and 11 senior centers) in New York, New York. The analysis focused on adults aged > or =65 years who lacked Medicaid coverage. Multivariable logistic regression was used to model program awareness as a function of information access (family/social support, attendance at senior or community centers and places of worship, viewing of live health insurance presentations, instrumental activities of daily living, site of medical care, computer use, and having a proxy decision maker for health insurance matters) and information-processing ability (education level, English proficiency, health literacy, and cognitive function). The main outcome measure was awareness of New York's state pharmaceutical assistance program (Elderly Pharmaceutical Insurance Coverage [EPIC
Big data and high-performance analytics in structural health monitoring for bridge management
NASA Astrophysics Data System (ADS)
Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed
2016-04-01
Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.
Mullins, Caitlyn R; Pairis-Garcia, Monique D; Campler, Magnus R; Anthony, Raymond; Johnson, Anna K; Coleman, Grahame J; Rault, Jean-Loup
2018-02-05
With extensive knowledge and training in the prevention, management, and treatment of disease conditions in animals, veterinarians play a critical role in ensuring good welfare on swine farms by training caretakers on the importance of timely euthanasia. To assist veterinarians and other industry professionals in training new and seasoned caretakers, an interactive computer-based training program was created. It consists of three modules, each containing five case studies, which cover three distinct production stages (breeding stock, piglets, and wean to grower-finisher pigs). Case study development was derived from five specific euthanasia criteria defined in the 2015 Common Swine Industry Audit, a nationally recognized auditing program used in the US. Case studies provide information regarding treatment history, clinical signs, and condition severity of the pig and prompt learners to make management decisions regarding pig treatment and care. Once a decision is made, feedback is provided so learners understand the appropriateness of their decision compared to current industry guidelines. In addition to training farm personnel, this program may also be a valuable resource if incorporated into veterinary, graduate, and continuing education curricula. This innovative tool represents the first interactive euthanasia-specific training program in the US swine industry and offers the potential to improve timely and humane on-farm pig euthanasia.
Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong
2010-01-01
In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy. PMID:22163641
Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong
2010-01-01
In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.
42 CFR 430.104 - Decisions that affect FFP.
Code of Federal Regulations, 2010 CFR
2010-10-01
... (CONTINUED) MEDICAL ASSISTANCE PROGRAMS GRANTS TO STATES FOR MEDICAL ASSISTANCE PROGRAMS Hearings on Conformity of State Medicaid Plans and Practice to Federal Requirements § 430.104 Decisions that affect FFP...
Artificial intelligence - New tools for aerospace project managers
NASA Technical Reports Server (NTRS)
Moja, D. C.
1985-01-01
Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.
Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E
2012-01-01
In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.
Alves-Pinto, A.; Sollini, J.; Sumner, C.J.
2012-01-01
Signal detection theory (SDT) provides a framework for interpreting psychophysical experiments, separating the putative internal sensory representation and the decision process. SDT was used to analyse ferret behavioural responses in a (yes–no) tone-in-noise detection task. Instead of measuring the receiver-operating characteristic (ROC), we tested SDT by comparing responses collected using two common psychophysical data collection methods. These (Constant Stimuli, Limits) differ in the set of signal levels presented within and across behavioural sessions. The results support the use of SDT as a method of analysis: SDT sensory component was unchanged between the two methods, even though decisions depended on the stimuli presented within a behavioural session. Decision criterion varied trial-by-trial: a ‘yes’ response was more likely after a correct rejection trial than a hit trial. Simulation using an SDT model with several decision components reproduced the experimental observations accurately, leaving only ∼10% of the variance unaccounted for. The model also showed that trial-by-trial dependencies were unlikely to influence measured psychometric functions or thresholds. An additional model component suggested that inattention did not contribute substantially. Further analysis showed that ferrets were changing their decision criteria, almost optimally, to maximise the reward obtained in a session. The data suggest trial-by-trial reward-driven optimization of the decision process. Understanding the factors determining behavioural responses is important for correlating neural activity and behaviour. SDT provides a good account of animal psychoacoustics, and can be validated using standard psychophysical methods and computer simulations, without recourse to ROC measurements. PMID:22698686
13 CFR 105.203 - SBA Assistance to person employing former SBA employee.
Code of Federal Regulations, 2010 CFR
2010-01-01
... nature to the Standards of Conduct Committee for final decision; otherwise, his or her decision is final... relationship of the former employee with the applicant concern; (2) The nature of the SBA Assistance requested... requested; and (4) Whether an apparent conflict of interest might exist if the SBA Assistance were granted. ...
Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul
2011-01-01
Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238
Computed-aided diagnosis (CAD) in the detection of breast cancer.
Dromain, C; Boyer, B; Ferré, R; Canale, S; Delaloge, S; Balleyguier, C
2013-03-01
Computer-aided detection (CAD) systems have been developed for interpretation to improve mammographic detection of breast cancer at screening by reducing the number of false-negative interpretation that can be caused by subtle findings, radiologist distraction and complex architecture. They use a digitized mammographic image that can be obtained from both screen-film mammography and full field digital mammography. Its performance in breast cancer detection is dependent on the performance of the CAD itself, the population to which it is applied and the radiologists who use it. There is a clear benefit to the use of CAD in less experienced radiologist and in detecting breast carcinomas presenting as microcalcifications. This review gives a detailed description CAD systems used in mammography and their performance in assistance of reading in screening mammography and as an alternative to double reading. Other CAD systems developed for MRI and ultrasound are also presented and discussed. Copyright © 2012. Published by Elsevier Ireland Ltd.
Diagnosis and management of solitary pulmonary nodules.
Jeong, Yeon Joo; Lee, Kyung Soo; Kwon, O Jung
2008-12-01
The advent of computed tomography (CT) screening with or without the help of computer-aided detection systems has increased the detection rate of solitary pulmonary nodules (SPNs), including that of early peripheral lung cancer. Helical dynamic (HD)CT, providing the information on morphologic and hemodynamic characteristics with high specificity and reasonably high accuracy, can be used for the initial assessment of SPNs. (18)F-fluorodeoxyglucose PET/CT is more sensitive at detecting malignancy than HDCT. Therefore, PET/CT may be selectively performed to characterize SPNs when HDCT gives an inconclusive diagnosis. Serial volume measurements are currently the most reliable methods for the tissue characterization of subcentimeter nodules. When malignant nodule is highly suspected for subcentimeter nodules, video-assisted thoracoscopic surgery nodule removal after nodule localization using the pulmonary nodule-marker system may be performed for diagnosis and treatment.
Influence of Polarity and Activation Energy in Microwave–Assisted Organic Synthesis (MAOS)
Rodríguez, Antonio M; Prieto, Pilar; de la Hoz, Antonio; Díaz-Ortiz, Ángel; Martín, D Raúl; García, José I
2015-01-01
The aim of this work was to determine the parameters that have decisive roles in microwave-assisted reactions and to develop a model, using computational chemistry, to predict a priori the type of reactions that can be improved under microwaves. For this purpose, a computational study was carried out on a variety of reactions, which have been reported to be improved under microwave irradiation. This comprises six types of reactions. The outcomes obtained in this study indicate that the most influential parameters are activation energy, enthalpy, and the polarity of all the species that participate. In addition to this, in most cases, slower reacting systems observe a much greater improvement under microwave irradiation. Furthermore, for these reactions, the presence of a polar component in the reaction (solvent, reagent, susceptor, etc.) is necessary for strong coupling with the electromagnetic radiation. We also quantified that an activation energy of 20–30 kcal mol−1 and a polarity (μ) between 7–20 D of the species involved in the process is required to obtain significant improvements under microwave irradiation. PMID:26246993
Kuhn, Stefan; Egert, Björn; Neumann, Steffen; Steinbeck, Christoph
2008-09-25
Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE) of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB. A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error. NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites.
Li, Ya-pin; Fang, Li-qun; Gao, Su-qing; Wang, Zhen; Gao, Hong-wei; Liu, Peng; Wang, Ze-Rui; Li, Yan-Li; Zhu, Xu-Guang; Li, Xin-Lou; Xu, Bo; Li, Yin-Jun; Yang, Hong; de Vlas, Sake J; Shi, Tao-Xing; Cao, Wu-Chun
2013-01-01
For years, emerging infectious diseases have appeared worldwide and threatened the health of people. The emergence and spread of an infectious-disease outbreak are usually unforeseen, and have the features of suddenness and uncertainty. Timely understanding of basic information in the field, and the collection and analysis of epidemiological information, is helpful in making rapid decisions and responding to an infectious-disease emergency. Therefore, it is necessary to have an unobstructed channel and convenient tool for the collection and analysis of epidemiologic information in the field. Baseline information for each county in mainland China was collected and a database was established by geo-coding information on a digital map of county boundaries throughout the country. Google Maps was used to display geographic information and to conduct calculations related to maps, and the 3G wireless network was used to transmit information collected in the field to the server. This study established a decision support system for the response to infectious-disease emergencies based on WebGIS and mobile services (DSSRIDE). The DSSRIDE provides functions including data collection, communication and analyses in real time, epidemiological detection, the provision of customized epidemiological questionnaires and guides for handling infectious disease emergencies, and the querying of professional knowledge in the field. These functions of the DSSRIDE could be helpful for epidemiological investigations in the field and the handling of infectious-disease emergencies. The DSSRIDE provides a geographic information platform based on the Google Maps application programming interface to display information of infectious disease emergencies, and transfers information between workers in the field and decision makers through wireless transmission based on personal computers, mobile phones and personal digital assistants. After a 2-year practice and application in infectious disease emergencies, the DSSRIDE is becoming a useful platform and is a useful tool for investigations in the field carried out by response sections and individuals. The system is suitable for use in developing countries and low-income districts.
Big Data, Smart Homes and Ambient Assisted Living
Wass, S.
2014-01-01
Summary Objectives To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data. Methods A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014. Results The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc. Conclusions The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today’s services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability. PMID:25123734
COMMUNITY CAPACITY BUILDING FOR REVITALIZATION AND SUSTAINABLE REDEVELOPMENT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Downing, Melinda; Rosenthall, John; Hudson, Michelle
2003-02-27
Capacity building programs help poor and disadvantaged communities to improve their ability to participate in the environmental decision-making processes. They encourage citizen involvement, and provide the tools that enable them to do so. Capacity building enables communities that would otherwise be excluded to participate in the process, leading to better, and more just decisions. The Department of Energy (DOE) continues to be committed to promoting environmental justice and involving its stakeholders more directly in the planning and decision-making process for environmental cleanup. DOE's Environmental Management Program (EM) is in full support of this commitment. Through its environmental justice project, EMmore » provides communities with the capacity to effectively contribute to a complex technical decision-making process by furnishing access to computers, the Internet, training and technical assistance. DOE's Dr. Samuel P. Massie Chairs of Excellence Program (Massie Chairs) function as technical advisors to many of these community projects. The Massie Chairs consist of nationally and internationally recognized engineers and scientists from nine Historically Black Colleges and Universities (HBCUs) and one Hispanic Serving Institution (HIS). This paper will discuss capacity building initiatives in various jurisdictions.« less
Wall, Stephen P; Mayorga, Oliver; Banfield, Christine E; Wall, Mark E; Aisic, Ilan; Auerbach, Carl; Gennis, Paul
2006-11-01
To develop software that categorizes electronic head computed tomography (CT) reports into groups useful for clinical decision rule research. Data were obtained from the Second National Emergency X-Radiography Utilization Study, a cohort of head injury patients having received head CT. CT reports were reviewed manually for presence or absence of clinically important subdural or epidural hematoma, defined as greater than 1.0 cm in width or causing mass effect. Manual categorization was done by 2 independent researchers blinded to each other's results. A third researcher adjudicated discrepancies. A random sample of 300 reports with radiologic abnormalities was selected for software development. After excluding reports categorized manually or by software as indeterminate (neither positive nor negative), we calculated sensitivity and specificity by using manual categorization as the standard. System efficiency was defined as the percentage of reports categorized as positive or negative, regardless of accuracy. Software was refined until analysis of the training data yielded sensitivity and specificity approximating 95% and efficiency exceeding 75%. To test the system, we calculated sensitivity, specificity, and efficiency, using the remaining 1,911 reports. Of the 1,911 reports, 160 had clinically important subdural or epidural hematoma. The software exhibited good agreement with manual categorization of all reports, including indeterminate ones (weighted kappa 0.62; 95% confidence interval [CI] 0.58 to 0.65). Sensitivity, specificity, and efficiency of the computerized system for identifying manual positives and negatives were 96% (95% CI 91% to 98%), 98% (95% CI 98% to 99%), and 79% (95% CI 77% to 80%), respectively. Categorizing head CT reports by computer for clinical decision rule research is feasible.
A decision support system for managing forest fire casualties.
Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos
2007-09-01
Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns.
Darby, Jonathan; Black, Jim; Morrison, David; Buising, Kirsty
2012-01-01
Information systems with clinical decision support (CDS) offer great potential to assist the co-ordination of patients with chronic diseases and to improve patient care. Despite this, few have entered routine clinical use. Tuberculosis (TB) is an infection of public health importance. It has complex interactions with many comorbid conditions, requires close supervised care and prolonged treatment for effective cure. These features make it suitable for use with an information management system with CDS features. In close consultation with key stakeholders, a clinical application was developed for the management of TB patients in Victoria. A formal usability assessment using semi-structured case-scenario based exercises was performed. Subjects were 12 individuals closely involved in the care of TB patients, including Infectious Diseases and Respiratory Physicians, and Public Health Nurses. Two researchers conducted the sessions, independently analysed responses and discrepancies compared to the voice record for validity. Despite varied computer experience, responses were positive regarding user interface and content. Data location was not always intuitive, however this improved with familiarity of the program. Decision support was considered valuable, with useful suggestions for expansion of these features. Automated reporting for correspondence and notification to the Health Department were felt worth the initial investment in data entry. An important workflow-based issue regarding dismissal of alerts and several errors were detected. Usability assessment validated many design elements of the system, provided a unique insight into workflow issues faced by users and hopefully will impact on its ultimate clinical utility.
Computer-assisted neurosurgical navigational system for transsphenoidal surgery--technical note.
Onizuka, M; Tokunaga, Y; Shibayama, A; Miyazaki, H
2001-11-01
Transsphenoidal surgery carries the risk of carotid artery injury even for very experienced neurosurgeons. The computer-assisted neurosurgical (CANS) navigational system was used to obtain more precise guidance, based on the axial and coronal images during the transsphenoidal approach for nine pituitary adenomas. The CANS navigator consists of a three-dimensional digitizer, a computer, and a graphic unit, which utilizes electromagnetic coupling technology to detect the spatial position of a suction tube attached to a magnetic sensor. Preoperatively, the magnetic resonance images are transferred and stored in the computer and the tip of the suction tube is shown on a real-time basis superimposed on the preoperative images. The CANS navigation system correctly displayed the surgical orientation and provided localization in all nine patients. No intraoperative complications were associated with the use of this system. However, outflow of cerebrospinal fluid during tumor removal may affect the accuracy, so the position of the probe when the tumor is removed must be accurately determined. The CANS navigator enables precise localization of the suction tube during the transsphenoidal approach and allows safer and less-invasive surgery.
Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System
NASA Astrophysics Data System (ADS)
Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.
2017-01-01
Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.
2013-10-01
latest (2004) National Health and Nutrition Examination Survey (NHANES) data demonstrated that 42.3% of patients with DM have A1Cs over 7% (22). The...military healthcare system (MHS) - where there is no cost to the patient for care and testing supplies - has similar results with hemoglobin A1C’s... Educators in both military and civilian health care settings (23), the vast majority of patients with DM are managed by primary care providers (PCPs
The role of networks and artificial intelligence in nanotechnology design and analysis.
Hudson, D L; Cohen, M E
2004-05-01
Techniques with their origins in artificial intelligence have had a great impact on many areas of biomedicine. Expert-based systems have been used to develop computer-assisted decision aids. Neural networks have been used extensively in disease classification and more recently in many bioinformatics applications including genomics and drug design. Network theory in general has proved useful in modeling all aspects of biomedicine from healthcare organizational structure to biochemical pathways. These methods show promise in applications involving nanotechnology both in the design phase and in interpretation of system functioning.
The Assisted Decision-Making (Capacity) Act 2015: what it is and why it matters.
Kelly, B D
2017-05-01
Ireland's Assisted Decision-Making (Capacity) Act 2015 was signed by President Higgins in December 2015 and scheduled for commencement in 2016. To explore the content and implications of the 2015 Act. Review of the 2015 Act and related literature. The 2015 Act places the "will and preferences" of persons with impaired mental capacity at the heart of decision-making relating to "personal welfare" (including healthcare) and "property and affairs". Capacity is to be "construed functionally" and interventions must be "for the benefit of the relevant person". The Act outlines three levels of decision-making assistance: "decision-making assistant", "co-decision-maker" (joint decision-maker) and "decision-making representative" (substitute decision-maker). There are procedures relating to "enduring power of attorney" and "advance healthcare directives"; in the case of the latter, a "refusal of treatment" can be legally binding, while a "request for a specific treatment" must "be taken into consideration". The 2015 Act is considerably more workable than the 2013 Bill that preceded it. Key challenges include the subtle decision-making required by patients, healthcare staff, Circuit Court judges and the director of the Decision Support Service; implementation of "advance healthcare directives", especially if they do not form part of a broader model of advance care planning (incorporating the flexibility required for unpredictable future circumstances); and the over-arching issue of logistics, as very many healthcare decisions are currently made in situations where the patient's capacity is impaired. A key challenge will lie in balancing the emphasis on autonomy with principles of beneficence, mutuality and care.
Morán-Sánchez, Inés; Luna, Aurelio; Pérez-Cárceles, Maria D
2016-11-30
Informed consent is a key element of ethical clinical research. Those with mental disorders may be at risk for impaired consent capacity. Problems with procedures may also contribute to patient's ´difficulties in understanding consent forms. The present investigation explores if a brief technologically based information presentation of the informed consent process may enhance psychiatric patients understanding and satisfaction. In this longitudinal, within-participants comparison study, patients who initially were judged to lack capacity to make research decisions (n=41) and a control group (n=47) were followed up. Decisional capacity, willingness to participate and cognitive and clinical scores were assessed at baseline and after receiving the computer-assisted enhanced consent. With sufficient cueing, patients with impaired research-related decision-making capacity at baseline were able to display enough understanding of the consent form. Patient satisfaction and willingness to participate also increased at follow up. Implications of these results for clinical practice and medical research involving people with mental disorders are discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Networks and games for precision medicine.
Biane, Célia; Delaplace, Franck; Klaudel, Hanna
2016-12-01
Recent advances in omics technologies provide the leverage for the emergence of precision medicine that aims at personalizing therapy to patient. In this undertaking, computational methods play a central role for assisting physicians in their clinical decision-making by combining data analysis and systems biology modelling. Complex diseases such as cancer or diabetes arise from the intricate interplay of various biological molecules. Therefore, assessing drug efficiency requires to study the effects of elementary perturbations caused by diseases on relevant biological networks. In this paper, we propose a computational framework called Network-Action Game applied to best drug selection problem combining Game Theory and discrete models of dynamics (Boolean networks). Decision-making is modelled using Game Theory that defines the process of drug selection among alternative possibilities, while Boolean networks are used to model the effects of the interplay between disease and drugs actions on the patient's molecular system. The actions/strategies of disease and drugs are focused on arc alterations of the interactome. The efficiency of this framework has been evaluated for drug prediction on a model of breast cancer signalling. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
A validated methodology for determination of laboratory instrument computer interface efficacy
NASA Astrophysics Data System (ADS)
1984-12-01
This report is intended to provide a methodology for determining when, and for which instruments, direct interfacing of laboratory instrument and laboratory computers is beneficial. This methodology has been developed to assist the Tri-Service Medical Information Systems Program Office in making future decisions regarding laboratory instrument interfaces. We have calculated the time savings required to reach a break-even point for a range of instrument interface prices and corresponding average annual costs. The break-even analyses used empirical data to estimate the number of data points run per day that are required to meet the break-even point. The results indicate, for example, that at a purchase price of $3,000, an instrument interface will be cost-effective if the instrument is utilized for at least 154 data points per day if operated in the continuous mode, or 216 points per day if operated in the discrete mode. Although this model can help to ensure that instrument interfaces are cost effective, additional information should be considered in making the interface decisions. A reduction in results transcription errors may be a major benefit of instrument interfacing.
Forest fire autonomous decision system based on fuzzy logic
NASA Astrophysics Data System (ADS)
Lei, Z.; Lu, Jianhua
2010-11-01
The proposed system integrates GPS / pseudolite / IMU and thermal camera in order to autonomously process the graphs by identification, extraction, tracking of forest fire or hot spots. The airborne detection platform, the graph-based algorithms and the signal processing frame are analyzed detailed; especially the rules of the decision function are expressed in terms of fuzzy logic, which is an appropriate method to express imprecise knowledge. The membership function and weights of the rules are fixed through a supervised learning process. The perception system in this paper is based on a network of sensorial stations and central stations. The sensorial stations collect data including infrared and visual images and meteorological information. The central stations exchange data to perform distributed analysis. The experiment results show that working procedure of detection system is reasonable and can accurately output the detection alarm and the computation of infrared oscillations.
Block, Annette; Debode, Frédéric; Grohmann, Lutz; Hulin, Julie; Taverniers, Isabel; Kluga, Linda; Barbau-Piednoir, Elodie; Broeders, Sylvia; Huber, Ingrid; Van den Bulcke, Marc; Heinze, Petra; Berben, Gilbert; Busch, Ulrich; Roosens, Nancy; Janssen, Eric; Žel, Jana; Gruden, Kristina; Morisset, Dany
2013-08-22
Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs' molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms.
2013-01-01
Background Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs’ molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. Description The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. Conclusions The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms. PMID:23965170
Mobile medical computing driven by the complexity of neurologic diagnosis.
Segal, Michael M
2006-07-01
Medical computing has been split between palm-sized computers optimized for mobility and desktop computers optimized for capability. This split was due to technology too immature to deliver both mobility and capability in the same computer and the lack of medical software that demanded both mobility and capability. Advances in hardware and software are ushering in an era in which fully capable computers will be available ubiquitously. As a result, medical practice, education and publishing will change. Medical practice will be improved by the use of software that not only assists with diagnosis but can do so at the bedside, where the doctor can act immediately upon suggestions such as useful findings to check. Medical education will shift away from a focus on details of unusual diseases and toward a focus on skills of physical examination and using computerized tools. Medical publishing, in contrast, will shift toward greater detail: it will be increasingly important to quantitate the frequency of findings in diseases and their time course since such information can have a major impact clinically when added to decision support software.
Morphological filtering and multiresolution fusion for mammographic microcalcification detection
NASA Astrophysics Data System (ADS)
Chen, Lulin; Chen, Chang W.; Parker, Kevin J.
1997-04-01
Mammographic images are often of relatively low contrast and poor sharpness with non-stationary background or clutter and are usually corrupted by noise. In this paper, we propose a new method for microcalcification detection using gray scale morphological filtering followed by multiresolution fusion and present a unified general filtering form called the local operating transformation for whitening filtering and adaptive thresholding. The gray scale morphological filters are used to remove all large areas that are considered as non-stationary background or clutter variations, i.e., to prewhiten images. The multiresolution fusion decision is based on matched filter theory. In addition to the normal matched filter, the Laplacian matched filter which is directly related through the wavelet transforms to multiresolution analysis is exploited for microcalcification feature detection. At the multiresolution fusion stage, the region growing techniques are used in each resolution level. The parent-child relations between resolution levels are adopted to make final detection decision. FROC is computed from test on the Nijmegen database.
Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection.
Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang
2018-01-15
In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes' (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10 -5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.
An integrated theory of attention and decision making in visual signal detection.
Smith, Philip L; Ratcliff, Roger
2009-04-01
The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in this task is described. The theory links visual encoding, masking, spatial attention, visual short-term memory (VSTM), and perceptual decision making in an integrated dynamic framework. The theory assumes that decisions are made by a diffusion process driven by a neurally plausible, shunting VSTM. The VSTM trace encodes the transient outputs of early visual filters in a durable form that is preserved for the time needed to make a decision. Attention increases the efficiency of VSTM encoding, either by increasing the rate of trace formation or by reducing the delay before trace formation begins. The theory provides a detailed, quantitative account of attentional effects in spatial cuing tasks at the level of response accuracy and the response time distributions. (c) 2009 APA, all rights reserved
KARL: A Knowledge-Assisted Retrieval Language. M.S. Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987
NASA Technical Reports Server (NTRS)
Dominick, Wayne D. (Editor); Triantafyllopoulos, Spiros
1985-01-01
Data classification and storage are tasks typically performed by application specialists. In contrast, information users are primarily non-computer specialists who use information in their decision-making and other activities. Interaction efficiency between such users and the computer is often reduced by machine requirements and resulting user reluctance to use the system. This thesis examines the problems associated with information retrieval for non-computer specialist users, and proposes a method for communicating in restricted English that uses knowledge of the entities involved, relationships between entities, and basic English language syntax and semantics to translate the user requests into formal queries. The proposed method includes an intelligent dictionary, syntax and semantic verifiers, and a formal query generator. In addition, the proposed system has a learning capability that can improve portability and performance. With the increasing demand for efficient human-machine communication, the significance of this thesis becomes apparent. As human resources become more valuable, software systems that will assist in improving the human-machine interface will be needed and research addressing new solutions will be of utmost importance. This thesis presents an initial design and implementation as a foundation for further research and development into the emerging field of natural language database query systems.
NASA Astrophysics Data System (ADS)
Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru
2007-03-01
Multislice CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multislice CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. Moreover, we have provided diagnostic assistance methods to medical screening specialists by using a lung cancer screening algorithm built into mobile helical CT scanner for the lung cancer mass screening done in the region without the hospital. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system.
One Shot Detection with Laplacian Object and Fast Matrix Cosine Similarity.
Biswas, Sujoy Kumar; Milanfar, Peyman
2016-03-01
One shot, generic object detection involves searching for a single query object in a larger target image. Relevant approaches have benefited from features that typically model the local similarity patterns. In this paper, we combine local similarity (encoded by local descriptors) with a global context (i.e., a graph structure) of pairwise affinities among the local descriptors, embedding the query descriptors into a low dimensional but discriminatory subspace. Unlike principal components that preserve global structure of feature space, we actually seek a linear approximation to the Laplacian eigenmap that permits us a locality preserving embedding of high dimensional region descriptors. Our second contribution is an accelerated but exact computation of matrix cosine similarity as the decision rule for detection, obviating the computationally expensive sliding window search. We leverage the power of Fourier transform combined with integral image to achieve superior runtime efficiency that allows us to test multiple hypotheses (for pose estimation) within a reasonably short time. Our approach to one shot detection is training-free, and experiments on the standard data sets confirm the efficacy of our model. Besides, low computation cost of the proposed (codebook-free) object detector facilitates rather straightforward query detection in large data sets including movie videos.
Dormann, H; Criegee-Rieck, M; Neubert, A; Egger, T; Levy, M; Hahn, E G; Brune, K
2004-02-01
To investigate the effectiveness of a computer monitoring system that detects adverse drug reactions (ADRs) by laboratory signals in gastroenterology. A prospective, 6-month, pharmaco-epidemiological survey was carried out on a gastroenterological ward at the University Hospital Erlangen-Nuremberg. Two methods were used to identify ADRs. (i) All charts were reviewed daily by physicians and clinical pharmacists. (ii) A computer monitoring system generated a daily list of automatic laboratory signals and alerts of ADRs, including patient data and dates of events. One hundred and nine ADRs were detected in 474 admissions (377 patients). The computer monitoring system generated 4454 automatic laboratory signals from 39 819 laboratory parameters tested, and issued 2328 alerts, 914 (39%) of which were associated with ADRs; 574 (25%) were associated with ADR-positive admissions. Of all the alerts generated, signals of hepatotoxicity (1255), followed by coagulation disorders (407) and haematological toxicity (207), were prevalent. Correspondingly, the prevailing ADRs were concerned with the metabolic and hepato-gastrointestinal system (61). The sensitivity was 91%: 69 of 76 ADR-positive patients were indicated by an alert. The specificity of alerts was increased from 23% to 76% after implementation of an automatic laboratory signal trend monitoring algorithm. This study shows that a computer monitoring system is a useful tool for the systematic and automated detection of ADRs in gastroenterological patients.
NASA Astrophysics Data System (ADS)
Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru
2008-03-01
Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The function to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and Success in login" effective. As a result, patients' private information is protected. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.
13 CFR 127.605 - What are the procedures for appealing an EDWOSB or WOSB status protest decision?
Code of Federal Regulations, 2010 CFR
2010-01-01
... appealing an EDWOSB or WOSB status protest decision? 127.605 Section 127.605 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION WOMEN-OWNED SMALL BUSINESS FEDERAL CONTRACT ASSISTANCE PROCEDURES Protests § 127.605 What are the procedures for appealing an EDWOSB or WOSB status protest decision? The protested...
ERIC Educational Resources Information Center
Evuleocha, Stevina U.; Ugbah, Steve D.; Law, Sweety
2009-01-01
Authors investigated perceptions of campus recruiters (N = 168) in the San Francisco Bay Area regarding the importance of 15 types of information they solicit from job applicants' references in making selection decisions. Results suggest campus recruiters should consider 10 types of information to assist them in making selection decisions. Results…
A Decision Support Model and Tool to Assist Financial Decision-Making in Universities
ERIC Educational Resources Information Center
Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive
2015-01-01
In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…
44 CFR Appendix A to Part 9 - Decision-making Process for E.O. 11988
Code of Federal Regulations, 2010 CFR
2010-10-01
... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Decision-making Process for E.O. 11988 A Appendix A to Part 9 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT..., App. A Appendix A to Part 9—Decision-making Process for E.O. 11988 EC02FE91.074 ...
Collaborative mining and interpretation of large-scale data for biomedical research insights.
Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis
2014-01-01
Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.
Collaborative Mining and Interpretation of Large-Scale Data for Biomedical Research Insights
Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis
2014-01-01
Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence. PMID:25268270
Security training with interactive laser-video-disk technology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilson, D.
1988-01-01
DOE, through its contractor EG and G Energy Measurements, Inc., has developed a state-of-the-art interactive-video system for use at the Department of Energy's Central Training Academy. Called the Security Training and Evaluation Shooting System (STRESS), the computer-driven decision shooting system employs the latest is laservideo-disk technology. STRESS is designed to provide realistic and stressful training for security inspectors employed by the DOE and its contractors. The system uses wide-screen video projection, sophisticated scenario-branching technology, and customized video scenarios especially designed for the DOE. Firing a weapon that has been modified to shoot ''laser bullets,'' and wearing a special vest thatmore » detects ''hits'': the security inspector encounters adversaries on the wide screen who can shoot or be shot by the inspector in scenarios that demand fast decisions. Based on those decisions, the computer provides instantaneous branching to different scenes, giving the inspector confrontational training with the realism and variability of real life.« less
Amyotrophic lateral sclerosis and assisted ventilation: how patients decide.
Lemoignan, Josée; Ells, Carolyn
2010-06-01
Throughout the course of their illness, people with amyotrophic lateral sclerosis (ALS) must make many treatment decisions; however, none has such a significant impact on quality of life and survival as decisions about assisted ventilation. The purpose of this study was to better understand the experience of decision-making about assisted ventilation for ALS patients. Using qualitative phenomenology methodology, 10 semi-structured interviews were conducted with persons with ALS and their caregivers to elicit factors that are pertinent to their decision-making process about assisted ventilation. Six main themes emerged from the interviews. (1) the meaning of the intervention - participants made a sharp distinction between non-invasive ventilation, which they viewed as a means to relieve symptoms of respiratory failure, and invasive ventilation, which they viewed as taking over their breathing and thereby saving their life when they otherwise would die, (2) the importance of context - including functional status, available supports, and financial implications, (3) the importance of values - with respect to communication, relationships, autonomy, life, and quality of life, (4) the effect of fears - particularly respiratory distress, chocking, running out of air, and the process of death itself, (5) the need for information - how use of assisted ventilation would impact daily life, how death from respiratory failure would occur, how caregivers and persons with ALS differ in their information needs and common misconceptions, and (6) adaptation to or acceptance of the intervention - a lengthy process that involved gradual familiarization with the equipment and its benefits. People with ALS and caregivers value autonomy in decision-making about assisted ventilation. Their decision-making process is neither wholly rational nor self-interested, and includes factors that health professionals should anticipate and address. Discussions about assisted ventilation and timing should be tailored to each individual and undertaken periodically.
Computer-Assisted Exposure Treatment for Flight Phobia
ERIC Educational Resources Information Center
Tortella-Feliu, Miguel; Bornas, Xavier; Llabres, Jordi
2008-01-01
This review introduces the state of the art in computer-assisted treatment for behavioural disorders. The core of the paper is devoted to describe one of these interventions providing computer-assisted exposure for flight phobia treatment, the Computer-Assisted Fear of Flying Treatment (CAFFT). The rationale, contents and structure of the CAFFT…
A Semantic Approach with Decision Support for Safety Service in Smart Home Management
Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli
2016-01-01
Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170
A Semantic Approach with Decision Support for Safety Service in Smart Home Management.
Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli
2016-08-03
Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.
Lützen, Ulf; Naumann, Carsten Maik; Marx, Marlies; Zhao, Yi; Jüptner, Michael; Baumann, René; Papp, László; Zsótér, Norbert; Aksenov, Alexey; Jünemann, Klaus-Peter; Zuhayra, Maaz
2016-09-07
Because of the increasing importance of computer-assisted post processing of image data in modern medical diagnostic we studied the value of an algorithm for assessment of single photon emission computed tomography/computed tomography (SPECT/CT)-data, which has been used for the first time for lymph node staging in penile cancer with non-palpable inguinal lymph nodes. In the guidelines of the relevant international expert societies, sentinel lymph node-biopsy (SLNB) is recommended as a diagnostic method of choice. The aim of this study is to evaluate the value of the afore-mentioned algorithm and in the clinical context the reliability and the associated morbidity of this procedure. Between 2008 and 2015, 25 patients with invasive penile cancer and inconspicuous inguinal lymph node status underwent SLNB after application of the radiotracer Tc-99m labelled nanocolloid. We recorded in a prospective approach the reliability and the complication rate of the procedure. In addition, we evaluated the results of an algorithm for SPECT/CT-data assessment of these patients. SLNB was carried out in 44 groins of 25 patients. In three patients, inguinal lymph node metastases were detected via SLNB. In one patient, bilateral lymph node recurrence of the groins occurred after negative SLNB. There was a false-negative rate of 4 % in relation to the number of patients (1/25), resp. 4.5 % in relation to the number of groins (2/44). Morbidity was 4 % in relation to the number of patients (1/25), resp. 2.3 % in relation to the number of groins (1/44). The results of computer-assisted assessment of SPECT/CT data for sentinel lymph node (SLN)-diagnostics demonstrated high sensitivity of 88.8 % and specificity of 86.7 %. SLNB is a very reliable method, associated with low morbidity. Computer-assisted assessment of SPECT/CT data of the SLN-diagnostics shows high sensitivity and specificity. While it cannot replace the assessment by medical experts, it can still provide substantial supplement and assistance.
Selection criteria and facilitation training for the study of groupware
NASA Technical Reports Server (NTRS)
Robichaux, Barry P.
1993-01-01
Computer support for planning and decision making groups is a growing trend in the 90s. Groupware is a name often applied to group software and has been defined as 'computer-based systems that support groups engaged in a common task (or goal) and that provide an interface to a shared environment'. Unlike most single-user software, groupware assists user groups in their collaboration, coordination, and communication efforts. This paper focuses on groupware to support the meeting process. These systems are often called group decision support systems (GDSS), electronic meeting systems (EMS), or group support systems (GSS). The term 'meeting support groupware' is used here to include any computer-based system to support meetings. In order to understand this technology, one must first understand groups, what they do and the problems they face, and groupware, a wide range of technology to support group work. Guidelines for selecting groups for study as part of an overall research plan are provided in this document. These were taken from the literature and from persons for whom the information in this paper was targeted. Also, guidelines for facilitation training are discussed. Familiarity with known and accepted techniques are the principle duties of the facilitator and any form of training must include practice in using these techniques.
Image-guided decision support system for pulmonary nodule classification in 3D thoracic CT images
NASA Astrophysics Data System (ADS)
Kawata, Yoshiki; Niki, Noboru; Ohmatsu, Hironobu; Kusumoto, Masahiro; Kakinuma, Ryutaro; Mori, Kiyoshi; Yamada, Kozo; Nishiyama, Hiroyuki; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki
2004-05-01
The purpose of this study is to develop an image-guided decision support system that assists decision-making in clinical differential diagnosis of pulmonary nodules. This approach retrieves and displays nodules that exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. In order to build the system, there are following issues that should be solved: 1) to categorize the nodule database with respect to morphological and internal features, 2) to quickly search nodule images similar to an indeterminate nodule from a large database, and 3) to reveal malignancy likelihood computed by using similar nodule images. Especially, the first problem influences the design of other issues. The successful categorization of nodule pattern might lead physicians to find important cues that characterize benign and malignant nodules. This paper focuses on an approach to categorize the nodule database with respect to nodule shape and CT density patterns inside nodule.
Merging spatially variant physical process models under an optimized systems dynamics framework.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cain, William O.; Lowry, Thomas Stephen; Pierce, Suzanne A.
The complexity of water resource issues, its interconnectedness to other systems, and the involvement of competing stakeholders often overwhelm decision-makers and inhibit the creation of clear management strategies. While a range of modeling tools and procedures exist to address these problems, they tend to be case specific and generally emphasize either a quantitative and overly analytic approach or present a qualitative dialogue-based approach lacking the ability to fully explore consequences of different policy decisions. The integration of these two approaches is needed to drive toward final decisions and engender effective outcomes. Given these limitations, the Computer Assisted Dispute Resolution systemmore » (CADRe) was developed to aid in stakeholder inclusive resource planning. This modeling and negotiation system uniquely addresses resource concerns by developing a spatially varying system dynamics model as well as innovative global optimization search techniques to maximize outcomes from participatory dialogues. Ultimately, the core system architecture of CADRe also serves as the cornerstone upon which key scientific innovation and challenges can be addressed.« less
Orhan, U.; Erdogmus, D.; Roark, B.; Oken, B.; Purwar, S.; Hild, K. E.; Fowler, A.; Fried-Oken, M.
2013-01-01
RSVP Keyboard™ is an electroencephalography (EEG) based brain computer interface (BCI) typing system, designed as an assistive technology for the communication needs of people with locked-in syndrome (LIS). It relies on rapid serial visual presentation (RSVP) and does not require precise eye gaze control. Existing BCI typing systems which uses event related potentials (ERP) in EEG suffer from low accuracy due to low signal-to-noise ratio. Henceforth, RSVP Keyboard™ utilizes a context based decision making via incorporating a language model, to improve the accuracy of letter decisions. To further improve the contributions of the language model, we propose recursive Bayesian estimation, which relies on non-committing string decisions, and conduct an offline analysis, which compares it with the existing naïve Bayesian fusion approach. The results indicate the superiority of the recursive Bayesian fusion and in the next generation of RSVP Keyboard™ we plan to incorporate this new approach. PMID:23366432
Design and implementation of intelligent electronic warfare decision making algorithm
NASA Astrophysics Data System (ADS)
Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun
2017-05-01
Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.
[Each person has to make their own individual decision - arguments for physician assisted suicide].
Posa, Andreas
2016-06-01
Since November 2015, businesslike assisted suicide is punishable in Germany. But who acts businesslike? The majority of the German population prefers to make own decisions about the circumstances of their arriving death, and many of them would also accept (physician) assisted suicide if necessary. Only a minority of physicians plead for prohibiting assisted suicide in general. In the end everyone should be able to take position on his own. No one is obliged to use or execute assisted suicide. © Georg Thieme Verlag KG Stuttgart · New York.
Personal digital assistant use by nurse practitioners: a descriptive study.
Stroud, Sally D; Smith, Carol A; Erkel, Elizabeth A
2009-01-01
We sought to describe the prevalence and patterns of use of personal digital assistants (PDAs) among active nurse practitioners (NPs). A descriptive correlational survey was conducted among NPs in the United States (N = 126). Participants were randomly selected from members of the American Academy of Nurse Practitioners who had listed a practice site on their application. Sixty-four percent of participants used PDAs. A drug reference was reported to be the most useful and frequently installed application. A large majority of PDA users believed that PDA use supported clinical decision making (91%), promoted patient safety (89%), and increased productivity (75%). Sixty-two percent predicted that PDA use would change their practice within the next 5 years. As innovative PDA applications with potential to improve patient outcomes become increasingly available, handheld computer skills will be a fundamental practice competency. To prevent errors in clinical decision making with quick access to PDA reference materials, NPs must critically evaluate the legitimacy and worth of PDA software programs. There is a critical need to evaluate the effectiveness of PDA use in clinical settings and develop an evidence base to guide use of the PDA in solving clinical problems.
Putzer, Gavin J; Park, Yangil
2012-01-01
The smartphone has emerged as an important technological device to assist physicians with medical decision making, clinical tasks, and other computing functions. A smartphone is a device that combines mobile telecommunication with Internet accessibility as well as word processing. Moreover, smartphones have additional features such as applications pertinent to clinical medicine and practice management. The purpose of this study was to investigate the innovation factors that affect a physician's decision to adopt an emerging mobile technological device such as a smartphone. The study sample consisted of 103 physicians from community hospitals and academic medical centers in the southeastern United States. Innovation factors are elements that affect an individual's attitude toward using and adopting an emerging technology. In our model, the innovation characteristics of compatibility, job relevance, the internal environment, observability, personal experience, and the external environment were all significant predictors of attitude toward using a smartphone. These influential innovation factors presumably are salient predictors of a physician's attitude toward using a smartphone to assist with clinical tasks. Health information technology devices such as smartphones offer promise as a means to improve clinical efficiency, medical quality, and care coordination and possibly reduce healthcare costs. PMID:22737094
The Application of Web-based Computer-assisted Instruction Courseware within Health Assessment
NASA Astrophysics Data System (ADS)
Xiuyan, Guo
Health assessment is a clinical nursing course and places emphasis on clinical skills. The application of computer-assisted instruction in the field of nursing teaching solved the problems in the traditional lecture class. This article stated teaching experience of web-based computer-assisted instruction, based upon a two-year study of computer-assisted instruction courseware use within the course health assessment. The computer-assisted instruction courseware could develop teaching structure, simulate clinical situations, create teaching situations and facilitate students study.
Banks, Victoria A; Stanton, Neville A
2015-01-01
Automated assistance in driving emergencies aims to improve the safety of our roads by avoiding or mitigating the effects of accidents. However, the behavioural implications of such systems remain unknown. This paper introduces the driver decision-making in emergencies (DDMiEs) framework to investigate how the level and type of automation may affect driver decision-making and subsequent responses to critical braking events using network analysis to interrogate retrospective verbalisations. Four DDMiE models were constructed to represent different levels of automation within the driving task and its effects on driver decision-making. Findings suggest that whilst automation does not alter the decision-making pathway (e.g. the processes between hazard detection and response remain similar), it does appear to significantly weaken the links between information-processing nodes. This reflects an unintended yet emergent property within the task network that could mean that we may not be improving safety in the way we expect. This paper contrasts models of driver decision-making in emergencies at varying levels of automation using the Southampton University Driving Simulator. Network analysis of retrospective verbalisations indicates that increasing the level of automation in driving emergencies weakens the link between information-processing nodes essential for effective decision-making.
Whole-genome CNV analysis: advances in computational approaches.
Pirooznia, Mehdi; Goes, Fernando S; Zandi, Peter P
2015-01-01
Accumulating evidence indicates that DNA copy number variation (CNV) is likely to make a significant contribution to human diversity and also play an important role in disease susceptibility. Recent advances in genome sequencing technologies have enabled the characterization of a variety of genomic features, including CNVs. This has led to the development of several bioinformatics approaches to detect CNVs from next-generation sequencing data. Here, we review recent advances in CNV detection from whole genome sequencing. We discuss the informatics approaches and current computational tools that have been developed as well as their strengths and limitations. This review will assist researchers and analysts in choosing the most suitable tools for CNV analysis as well as provide suggestions for new directions in future development.
Rauscher, Isabel; Düwel, Charlotte; Haller, Bernhard; Rischpler, Christoph; Heck, Matthias M; Gschwend, Jürgen E; Schwaiger, Markus; Maurer, Tobias; Eiber, Matthias
2018-05-01
Recently, 68 Ga-labeled prostate-specific membrane antigen (PSMA)-ligand positron-emission tomography (PET) imaging has been shown to improve detection rates in recurrent prostate cancer (PC). However, published studies include only small patient numbers at low prostate-specific antigen (PSA) values. For this study, 272 consecutive patients with biochemical recurrence after radical prostatectomy and PSA value between 0.2 and 1ng/ml were included. The 68 Ga-PSMA-ligand PET/computed tomography (CT) was evaluated, and detection rates were determined and correlated to various clinical variables using univariate and multivariable analyses. Subgroups of patients with very low (0.2-0.5ng/ml) and low (>0.5-1.0ng/ml) PSA values were analyzed. In total, lesions indicative of PC recurrence were detected in 55% (74/134) and 74% (102/138) with very low and low PSA values, respectively. Main sites of recurrence were pelvic or retroperitoneal lymph nodes metastases, followed by local recurrence and bone metastases with higher probability in the low versus very low PSA subgroup. Detection rates significantly increased with higher PSA values, primary pT≥3a, primary pN+ disease, grade group ≥4, previous radiation therapy, and concurrent androgen deprivation therapy (ADT) in univariate analysis. In a multivariable logistic regression model, concurrent ADT and PSA values were identified as most relevant predictors of positive 68 Ga-PSMA-ligand PET/CT. Further, prediction nomograms were established, which may help in estimating pretest PSMA-ligand PET positivity in clinical practice. In our study, 68 Ga-labeled prostate-specific membrane antigen (PSMA)-ligand positron-emission tomography (PET)/computed tomography (CT) detected recurrent disease after radical prostatectomy in 55% (74/134) and 74% (102/138) of patients with very low (0.2-0.5ng/ml) and low (>0.5-1.0ng/ml) prostate-specific antigen values, respectively. On the basis of these data, it seems reasonable to perform 68 Ga-PSMA-ligand PET/CT also in patients with early biochemical recurrence, as it can tailor further therapy decisions (eg, local vs systemic treatment). The established prediction nomograms can further assist urologists in discussions on the use of 68 Ga-PSMA-ligand PET/CT with their patients in specific clinical settings. Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.
Development of a theory-guided pan-European computer-assisted safer sex intervention.
Nöstlinger, Christiana; Borms, Ruth; Dec-Pietrowska, Joanna; Dias, Sonia; Rojas, Daniela; Platteau, Tom; Vanden Berghe, Wim; Kok, Gerjo
2016-12-01
HIV is a growing public health problem in Europe, with men-having-sex-with-men and migrants from endemic regions as the most affected key populations. More evidence on effective behavioral interventions to reduce sexual risk is needed. This article describes the systematic development of a theory-guided computer-assisted safer sex intervention, aiming at supporting people living with HIV in sexual risk reduction. We applied the Intervention Mapping (IM) protocol to develop this counseling intervention in the framework of a European multicenter study. We conducted a needs assessment guided by the information-motivation-behavioral (IMB) skills model, formulated change objectives and selected theory-based methods and practical strategies, i.e. interactive computer-assisted modules as supporting tools for provider-delivered counseling. Theoretical foundations were the IMB skills model, social cognitive theory and the transtheoretical model, complemented by dual process models of affective decision making to account for the specifics of sexual behavior. The counseling approach for delivering three individual sessions was tailored to participants' needs and contexts, adopting elements of motivational interviewing and cognitive-behavioral therapy. We implemented and evaluated the intervention using a randomized controlled trial combined with a process evaluation. IM provided a useful framework for developing a coherent intervention for heterogeneous target groups, which was feasible and effective across the culturally diverse settings. This article responds to the need for transparent descriptions of the development and content of evidence-based behavior change interventions as potential pillars of effective combination prevention strategies. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Design Principles for Computer-Assisted Instruction in Histology Education: An Exploratory Study
ERIC Educational Resources Information Center
Deniz, Hasan; Cakir, Hasan
2006-01-01
The purpose of this paper is to describe the development process and the key components of a computer-assisted histology material. Computer-assisted histology material is designed to supplement traditional histology education in a large Midwestern university. Usability information of the computer-assisted instruction (CAI) material was obtained…
Code of Federal Regulations, 2010 CFR
2010-10-01
... 45 Public Welfare 2 2010-10-01 2010-10-01 false Computing the assistance payment under... FINANCIAL ASSISTANCE PROGRAMS § 233.35 Computing the assistance payment under retrospective budgeting after... shall be computed retrospectively, i.e., shall be based on income and other relevant circumstances in...
Wang, Shu-Jang; Lai, Pei-Yu; Liou, Siao-Ying; Ko, Wen-Chien; Ko, Nai-Ying
2012-10-01
Family members play an important role in the process of writing advance directives. Homosexual men infected with HIV often wish to authorize their intimate same-sex partner or friends rather than immediate family members to make medical decisions on their behalf. Although same-sex marriage is currently illegal in Taiwan, HIV infected homosexual patients are able to write advance directives appointing their same-sex partner to be their surrogate decision maker for end-of-life medical decisions. This case report describes an experience assisting a homosexual patient with HIV to write his advance directives. The nurse assisted the patient and his partner to make a self-determined decision not to resuscitate. Family conferences held to discuss the patient's decisions regarding resuscitation helped legitimize his partner's primary role in making end-of-life healthcare decisions on his behalf. As an advocate for patient rights, nurses should understand the law as it relates to homosexuality and end-of-life decision making, inform patients on the durable power of autonomy, and help execute their advance directives.
Dalaba, Maxwell Ayindenaba; Akweongo, Patricia; Williams, John; Saronga, Happiness Pius; Tonchev, Pencho; Sauerborn, Rainer; Mensah, Nathan; Blank, Antje; Kaltschmidt, Jens; Loukanova, Svetla
2014-01-01
This study analyzed cost of implementing computer-assisted Clinical Decision Support System (CDSS) in selected health care centres in Ghana. A descriptive cross sectional study was conducted in the Kassena-Nankana district (KND). CDSS was deployed in selected health centres in KND as an intervention to manage patients attending antenatal clinics and the labour ward. The CDSS users were mainly nurses who were trained. Activities and associated costs involved in the implementation of CDSS (pre-intervention and intervention) were collected for the period between 2009-2013 from the provider perspective. The ingredients approach was used for the cost analysis. Costs were grouped into personnel, trainings, overheads (recurrent costs) and equipment costs (capital cost). We calculated cost without annualizing capital cost to represent financial cost and cost with annualizing capital costs to represent economic cost. Twenty-two trained CDSS users (at least 2 users per health centre) participated in the study. Between April 2012 and March 2013, users managed 5,595 antenatal clients and 872 labour clients using the CDSS. We observed a decrease in the proportion of complications during delivery (pre-intervention 10.74% versus post-intervention 9.64%) and a reduction in the number of maternal deaths (pre-intervention 4 deaths versus post-intervention 1 death). The overall financial cost of CDSS implementation was US$23,316, approximately US$1,060 per CDSS user trained. Of the total cost of implementation, 48% (US$11,272) was pre-intervention cost and intervention cost was 52% (US$12,044). Equipment costs accounted for the largest proportion of financial cost: 34% (US$7,917). When economic cost was considered, total cost of implementation was US$17,128-lower than the financial cost by 26.5%. The study provides useful information in the implementation of CDSS at health facilities to enhance health workers' adherence to practice guidelines and taking accurate decisions to improve maternal health care.
Azadmanjir, Zahra; Safdari, Reza; Ghazisaeedi, Marjan; Mokhtaran, Mehrshad; Kameli, Mohammad Esmail
2017-01-01
Introduction: Accurate coded data in the healthcare are critical. Computer-Assisted Coding (CAC) is an effective tool to improve clinical coding in particular when a new classification will be developed and implemented. But determine the appropriate method for development need to consider the specifications of existing CAC systems, requirements for each type, our infrastructure and also, the classification scheme. Aim: The aim of the study was the development of a decision model for determining accurate code of each medical intervention in Iranian Classification of Health Interventions (IRCHI) that can be implemented as a suitable CAC system. Methods: first, a sample of existing CAC systems was reviewed. Then feasibility of each one of CAC types was examined with regard to their prerequisites for their implementation. The next step, proper model was proposed according to the structure of the classification scheme and was implemented as an interactive system. Results: There is a significant relationship between the level of assistance of a CAC system and integration of it with electronic medical documents. Implementation of fully automated CAC systems is impossible due to immature development of electronic medical record and problems in using language for medical documenting. So, a model was proposed to develop semi-automated CAC system based on hierarchical relationships between entities in the classification scheme and also the logic of decision making to specify the characters of code step by step through a web-based interactive user interface for CAC. It was composed of three phases to select Target, Action and Means respectively for an intervention. Conclusion: The proposed model was suitable the current status of clinical documentation and coding in Iran and also, the structure of new classification scheme. Our results show it was practical. However, the model needs to be evaluated in the next stage of the research. PMID:28883671
Ludolph, Ingo; Arkudas, Andreas; Schmitz, Marweh; Boos, Anja M; Taeger, Christian D; Rother, Ulrich; Horch, Raymund E; Beier, Justus P
2016-10-01
The aim of this prospective study was to assess the correlation of flap perfusion analysis based on laser-assisted Indocyanine Green (ICG) angiography with combined laser Doppler spectrophotometry in autologous breast reconstruction using free DIEP/ms-TRAM flaps. Between February 2014 and July 2015, 35 free DIEP/ms-TRAM flaps were included in this study. Besides the clinical evaluation of flaps, intraoperative perfusion dynamics were assessed by means of laser-assisted ICG angiography and post-capillary oxygen saturation and relative haemoglobin content (rHb) using combined laser Doppler spectrophotometry. Correlation of the aforementioned parameters was analysed, as well as the impact on flap design and postoperative complications. Flap survival rate was 100%. There were no partial flap losses. In three cases, flap design was based on the angiography, contrary to clinical evaluation and spectrophotometry. The final decision on the inclusion of flap areas was based on the angiographic perfusion pattern. Angiography and spectrophotometry showed a correlation in most of the cases regarding tissue perfusion, post-capillary oxygen saturation and relative haemoglobin content. Laser-assisted ICG angiography is a useful tool for intraoperative evaluation of flap perfusion in autologous breast reconstruction with DIEP/ms-TRAM flaps, especially in decision making in cases where flap perfusion is not clearly assessable by clinical signs and exact determination of well-perfused flap margins is difficult to obtain. It provides an objective real-time analysis of flap perfusion, with high sensitivity for the detection of poorly perfused flap areas. Concerning the topographical mapping of well-perfused flap areas, laser-assisted angiography is superior to combined laser Doppler spectrophotometry. Copyright © 2016 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Dammak, Salma; Palma, David; Mattonen, Sarah; Senan, Suresh; Ward, Aaron D.
2018-02-01
Stereotactic ablative radiotherapy (SABR) is the standard treatment recommendation for Stage I non-small cell lung cancer (NSCLC) patients who are inoperable or who refuse surgery. This option is well tolerated by even unfit patients and has a low recurrence risk post-treatment. However, SABR induces changes in the lung parenchyma that can appear similar to those of recurrence, and the difference between the two at an early follow-up time point is not easily distinguishable for an expert physician. We hypothesized that a radiomics signature derived from standard-of-care computed tomography (CT) imaging can detect cancer recurrence within six months of SABR treatment. This study reports on the design phase of our work, with external validation planned in future work. In this study, we performed cross-validation experiments with four feature selection approaches and seven classifiers on an 81-patient data set. We extracted 104 radiomics features from the consolidative and the peri-consolidative regions on the follow-up CT scans. The best results were achieved using the sum of estimated Mahalanobis distances (Maha) for supervised forward feature selection and a trainable automatic radial basis support vector classifier (RBSVC). This system produced an area under the receiver operating characteristic curve (AUC) of 0.84, an error rate of 16.4%, a false negative rate of 12.7%, and a false positive rate of 20.0% for leaveone patient out cross-validation. This suggests that once validated on an external data set, radiomics could reliably detect post-SABR recurrence and form the basis of a tool assisting physicians in making salvage treatment decisions.
NASA Astrophysics Data System (ADS)
Chaisaowong, Kraisorn; Kraus, Thomas
2014-03-01
Pleural thickenings can be caused by asbestos exposure and may evolve into malignant pleural mesothelioma. While an early diagnosis plays the key role to an early treatment, and therefore helping to reduce morbidity, the growth rate of a pleural thickening can be in turn essential evidence to an early diagnosis of the pleural mesothelioma. The detection of pleural thickenings is today done by a visual inspection of CT data, which is time-consuming and underlies the physician's subjective judgment. Computer-assisted diagnosis systems to automatically assess pleural mesothelioma have been reported worldwide. But in this paper, an image analysis pipeline to automatically detect pleural thickenings and measure their volume is described. We first delineate automatically the pleural contour in the CT images. An adaptive surface-base smoothing technique is then applied to the pleural contours to identify all potential thickenings. A following tissue-specific topology-oriented detection based on a probabilistic Hounsfield Unit model of pleural plaques specify then the genuine pleural thickenings among them. The assessment of the detected pleural thickenings is based on the volumetry of the 3D model, created by mesh construction algorithm followed by Laplace-Beltrami eigenfunction expansion surface smoothing technique. Finally, the spatiotemporal matching of pleural thickenings from consecutive CT data is carried out based on the semi-automatic lung registration towards the assessment of its growth rate. With these methods, a new computer-assisted diagnosis system is presented in order to assure a precise and reproducible assessment of pleural thickenings towards the diagnosis of the pleural mesothelioma in its early stage.
Analysis And Assistant Planning System Ofregional Agricultural Economic Inform
NASA Astrophysics Data System (ADS)
Han, Jie; Zhang, Junfeng
For the common problems existed in regional development and planning, we try to design a decision support system for assisting regional agricultural development and alignment as a decision-making tool for local government and decision maker. The analysis methods of forecast, comparative advantage, liner programming and statistical analysis are adopted. According to comparative advantage theory, the regional advantage can be determined by calculating and comparing yield advantage index (YAI), Scale advantage index (SAI), Complicated advantage index (CAI). Combining with GIS, agricultural data are presented as a form of graph such as area, bar and pie to uncover the principle and trend for decision-making which can't be found in data table. This system provides assistant decisions for agricultural structure adjustment, agro-forestry development and planning, and can be integrated to information technologies such as RS, AI and so on.
SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE
Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...
Closed-Loop- and Decision-Assist-Guided Fluid Therapy of Human Hemorrhage.
Hundeshagen, Gabriel; Kramer, George C; Ribeiro Marques, Nicole; Salter, Michael G; Koutrouvelis, Aristides K; Li, Husong; Solanki, Daneshvari R; Indrikovs, Alexander; Seeton, Roger; Henkel, Sheryl N; Kinsky, Michael P
2017-10-01
We sought to evaluate the efficacy, efficiency, and physiologic consequences of automated, endpoint-directed resuscitation systems and compare them to formula-based bolus resuscitation. Experimental human hemorrhage and resuscitation. Clinical research laboratory. Healthy volunteers. Subjects (n = 7) were subjected to hemorrhage and underwent a randomized fluid resuscitation scheme on separate visits 1) formula-based bolus resuscitation; 2) semiautonomous (decision assist) fluid administration; and 3) fully autonomous (closed loop) resuscitation. Hemodynamic variables, volume shifts, fluid balance, and cardiac function were monitored during hemorrhage and resuscitation. Treatment modalities were compared based on resuscitation efficacy and efficiency. All approaches achieved target blood pressure by 60 minutes. Following hemorrhage, the total amount of infused fluid (bolus resuscitation: 30 mL/kg, decision assist: 5.6 ± 3 mL/kg, closed loop: 4.2 ± 2 mL/kg; p < 0.001), plasma volume, extravascular volume (bolus resuscitation: 17 ± 4 mL/kg, decision assist: 3 ± 1 mL/kg, closed loop: -0.3 ± 0.3 mL/kg; p < 0.001), body weight, and urinary output remained stable under decision assist and closed loop and were significantly increased under bolus resuscitation. Mean arterial pressure initially decreased further under bolus resuscitation (-10 mm Hg; p < 0.001) and was lower under bolus resuscitation than closed loop at 20 minutes (bolus resuscitation: 57 ± 2 mm Hg, closed loop: 69 ± 4 mm Hg; p = 0.036). Colloid osmotic pressure (bolus resuscitation: 19.3 ± 2 mm Hg, decision assist, closed loop: 24 ± 0.4 mm Hg; p < 0.05) and hemoglobin concentration were significantly decreased after bolus fluid administration. We define efficacy of decision-assist and closed-loop resuscitation in human hemorrhage. In comparison with formula-based bolus resuscitation, both semiautonomous and autonomous approaches were more efficient in goal-directed resuscitation of hemorrhage. They provide favorable conditions for the avoidance of over-resuscitation and its adverse clinical sequelae. Decision-assist and closed-loop resuscitation algorithms are promising technological solutions for constrained environments and areas of limited resources.
Fault trees for decision making in systems analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lambert, Howard E.
1975-10-09
The application of fault tree analysis (FTA) to system safety and reliability is presented within the framework of system safety analysis. The concepts and techniques involved in manual and automated fault tree construction are described and their differences noted. The theory of mathematical reliability pertinent to FTA is presented with emphasis on engineering applications. An outline of the quantitative reliability techniques of the Reactor Safety Study is given. Concepts of probabilistic importance are presented within the fault tree framework and applied to the areas of system design, diagnosis and simulation. The computer code IMPORTANCE ranks basic events and cut setsmore » according to a sensitivity analysis. A useful feature of the IMPORTANCE code is that it can accept relative failure data as input. The output of the IMPORTANCE code can assist an analyst in finding weaknesses in system design and operation, suggest the most optimal course of system upgrade, and determine the optimal location of sensors within a system. A general simulation model of system failure in terms of fault tree logic is described. The model is intended for efficient diagnosis of the causes of system failure in the event of a system breakdown. It can also be used to assist an operator in making decisions under a time constraint regarding the future course of operations. The model is well suited for computer implementation. New results incorporated in the simulation model include an algorithm to generate repair checklists on the basis of fault tree logic and a one-step-ahead optimization procedure that minimizes the expected time to diagnose system failure.« less
Blanson Henkemans, O. A.; Rogers, W. A.; Fisk, A. D.; Neerincx, M. A.; Lindenberg, J.; van der Mast, C. A. P. G.
2014-01-01
Summary Objectives We developed an adaptive computer assistant for the supervision of diabetics’ self-care, to support limiting illness and need for acute treatment, and improve health literacy. This assistant monitors self-care activities logged in the patient’s electronic diary. Accordingly, it provides context-aware feedback. The objective was to evaluate whether older adults in general can make use of the computer assistant and to compare an adaptive computer assistant with a fixed one, concerning its usability and contribution to health literacy. Methods We conducted a laboratory experiment in the Georgia Tech Aware Home wherein 28 older adults participated in a usability evaluation of the computer assistant, while engaged in scenarios reflecting normal and health-critical situations. We evaluated the assistant on effectiveness, efficiency, satisfaction, and educational value. Finally, we studied the moderating effects of the subjects’ personal characteristics. Results Logging self-care tasks and receiving feedback from the computer assistant enhanced the subjects’ knowledge of diabetes. The adaptive assistant was more effective in dealing with normal and health-critical situations, and, generally, it led to more time efficiency. Subjects’ personal characteristics had substantial effects on the effectiveness and efficiency of the two computer assistants. Conclusions Older adults were able to use the adaptive computer assistant. In addition, it had a positive effect on the development of health literacy. The assistant has the potential to support older diabetics’ self care while maintaining quality of life. PMID:18213433
Boone, Darren; Mallett, Susan; McQuillan, Justine; Taylor, Stuart A.; Altman, Douglas G.; Halligan, Steve
2015-01-01
Objectives To quantify the incremental benefit of computer-assisted-detection (CAD) for polyps, for inexperienced readers versus experienced readers of CT colonography. Methods 10 inexperienced and 16 experienced radiologists interpreted 102 colonography studies unassisted and with CAD utilised in a concurrent paradigm. They indicated any polyps detected on a study sheet. Readers’ interpretations were compared against a ground-truth reference standard: 46 studies were normal and 56 had at least one polyp (132 polyps in total). The primary study outcome was the difference in CAD net benefit (a combination of change in sensitivity and change in specificity with CAD, weighted towards sensitivity) for detection of patients with polyps. Results Inexperienced readers’ per-patient sensitivity rose from 39.1% to 53.2% with CAD and specificity fell from 94.1% to 88.0%, both statistically significant. Experienced readers’ sensitivity rose from 57.5% to 62.1% and specificity fell from 91.0% to 88.3%, both non-significant. Net benefit with CAD assistance was significant for inexperienced readers but not for experienced readers: 11.2% (95%CI 3.1% to 18.9%) versus 3.2% (95%CI -1.9% to 8.3%) respectively. Conclusions Concurrent CAD resulted in a significant net benefit when used by inexperienced readers to identify patients with polyps by CT colonography. The net benefit was nearly four times the magnitude of that observed for experienced readers. Experienced readers did not benefit significantly from concurrent CAD. PMID:26355745
Perceptual Decision Making in Rodents, Monkeys, and Humans.
Hanks, Timothy D; Summerfield, Christopher
2017-01-04
Perceptual decision making is the process by which animals detect, discriminate, and categorize information from the senses. Over the past two decades, understanding how perceptual decisions are made has become a central theme in the neurosciences. Exceptional progress has been made by recording from single neurons in the cortex of the macaque monkey and using computational models from mathematical psychology to relate these neural data to behavior. More recently, however, the range of available techniques and paradigms has dramatically broadened, and researchers have begun to harness new approaches to explore how rodents and humans make perceptual decisions. The results have illustrated some striking convergences with findings from the monkey, but also raised new questions and provided new theoretical insights. In this review, we summarize key findings, and highlight open challenges, for understanding perceptual decision making in rodents, monkeys, and humans. Copyright © 2017 Elsevier Inc. All rights reserved.
Zendehrouh, Sareh
2015-11-01
Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.
High-resolution computer-aided moire
NASA Astrophysics Data System (ADS)
Sciammarella, Cesar A.; Bhat, Gopalakrishna K.
1991-12-01
This paper presents a high resolution computer assisted moire technique for the measurement of displacements and strains at the microscopic level. The detection of micro-displacements using a moire grid and the problem associated with the recovery of displacement field from the sampled values of the grid intensity are discussed. A two dimensional Fourier transform method for the extraction of displacements from the image of the moire grid is outlined. An example of application of the technique to the measurement of strains and stresses in the vicinity of the crack tip in a compact tension specimen is given.
Geometry-based ensembles: toward a structural characterization of the classification boundary.
Pujol, Oriol; Masip, David
2009-06-01
This paper introduces a novel binary discriminative learning technique based on the approximation of the nonlinear decision boundary by a piecewise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points-points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and nonlinear behavior is obtained. The simplicity of the method allows its extension to cope with some of today's machine learning challenges, such as online learning, large-scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database, comparing with several state-of-the-art classification techniques. Finally, we apply our technique in online and large-scale scenarios and in six real-life computer vision and pattern recognition problems: gender recognition based on face images, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease myocardial damage severity detection, old musical scores clef classification, and action recognition using 3D accelerometer data from a wearable device. The results are promising and this paper opens a line of research that deserves further attention.
Deep neural network-based computer-assisted detection of cerebral aneurysms in MR angiography.
Nakao, Takahiro; Hanaoka, Shouhei; Nomura, Yukihiro; Sato, Issei; Nemoto, Mitsutaka; Miki, Soichiro; Maeda, Eriko; Yoshikawa, Takeharu; Hayashi, Naoto; Abe, Osamu
2018-04-01
The usefulness of computer-assisted detection (CAD) for detecting cerebral aneurysms has been reported; therefore, the improved performance of CAD will help to detect cerebral aneurysms. To develop a CAD system for intracranial aneurysms on unenhanced magnetic resonance angiography (MRA) images based on a deep convolutional neural network (CNN) and a maximum intensity projection (MIP) algorithm, and to demonstrate the usefulness of the system by training and evaluating it using a large dataset. Retrospective study. There were 450 cases with intracranial aneurysms. The diagnoses of brain aneurysms were made on the basis of MRA, which was performed as part of a brain screening program. Noncontrast-enhanced 3D time-of-flight (TOF) MRA on 3T MR scanners. In our CAD, we used a CNN classifier that predicts whether each voxel is inside or outside aneurysms by inputting MIP images generated from a volume of interest (VOI) around the voxel. The CNN was trained in advance using manually inputted labels. We evaluated our method using 450 cases with intracranial aneurysms, 300 of which were used for training, 50 for parameter tuning, and 100 for the final evaluation. Free-response receiver operating characteristic (FROC) analysis. Our CAD system detected 94.2% (98/104) of aneurysms with 2.9 false positives per case (FPs/case). At a sensitivity of 70%, the number of FPs/case was 0.26. We showed that the combination of a CNN and an MIP algorithm is useful for the detection of intracranial aneurysms. 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:948-953. © 2017 International Society for Magnetic Resonance in Medicine.
Clinical decision making using teleradiology in urology.
Lee, B R; Allaf, M; Moore, R; Bohlman, M; Wang, G M; Bishoff, J T; Jackman, S V; Cadeddu, J A; Jarrett, T W; Khazan, R; Kavoussi, L R
1999-01-01
Using a personal computer-based teleradiology system, we compared accuracy, confidence, and diagnostic ability in the interpretation of digitized radiographs to determine if teleradiology-imported studies convey sufficient information to make relevant clinical decisions involving urology. Variables of diagnostic accuracy, confidence, image quality, interpretation, and the impact of clinical decisions made after viewing digitized radiographs were compared with those of original radiographs. We evaluated 956 radiographs that included 94 IV pyelograms, four voiding cystourethrograms, and two nephrostograms. The radiographs were digitized and transferred over an Ethernet network to a remote personal computer-based viewing station. The digitized images were viewed by urologists and graded according to confidence in making a diagnosis, image quality, diagnostic difficulty, clinical management based on the image itself, and brief patient history. The hard-copy radiographs were then interpreted immediately afterward, and diagnostic decisions were reassessed. All analog radiographs were reviewed by an attending radiologist. Ninety-seven percent of the decisions made from the digitized radiographs did not change after reviewing conventional radiographs of the same case. When comparing the variables of clinical confidence, quality of the film on the teleradiology system versus analog films, and diagnostic difficulty, we found no statistical difference (p > .05) between the two techniques. Overall accuracy in interpreting the digitized images on the teleradiology system was 88% by urologists compared with that of the attending radiologist's interpretation of the analog radiographs. However, urologists detected findings on five (5%) analog radiographs that had been previously unreported by the radiologist. Viewing radiographs transmitted to a personal computer-based viewing station is an appropriate means of reviewing films with sufficient quality on which to base clinical decisions. Our focus was whether decisions made after viewing the transmitted radiographs would change after viewing the hard-copy images of the same case. In 97% of the cases, the decision did not change. In those cases in which management was altered, recommendation of further imaging studies was the most common factor.
Towards an Intelligent Textbook of Neurology
Reggia, James A.; Pula, Thaddeus P.; Price, Thomas R.; Perricone, Barry T.
1980-01-01
We define an intelligent textbook of medicine to be a computer system that: (1) provides for storage and selective retrieval of synthesized clinical knowledge for reference purposes; and (2) supports the application by computer of its knowledge to patient information to assist physicians with decision making. This paper describes an experimental system called KMS (a Knowledge Management System) for creating and using intelligent medical textbooks. KMS is domain-independent, supports multiple inference methods and representation languages, and is designed for direct use by physicians during the knowledge acquisition process. It is presented here in the context of the development of an Intelligent Textbook of Neurology. We suggest that KMS has the potential to overcome some of the problems that have inhibited the use of knowledge-based systems by physicians in the past.
FRIEND: a brain-monitoring agent for adaptive and assistive systems.
Morris, Alexis; Ulieru, Mihaela
2012-01-01
This paper presents an architectural design for adaptive-systems agents (FRIEND) that use brain state information to make more effective decisions on behalf of a user; measuring brain context versus situational demands. These systems could be useful for alerting users to cognitive workload levels or fatigue, and could attempt to compensate for higher cognitive activity by filtering noise information. In some cases such systems could also share control of devices, such as pulling over in an automated vehicle. These aim to assist people in everyday systems to perform tasks better and be more aware of internal states. Achieving a functioning system of this sort is a challenge, involving a unification of brain- computer-interfaces, human-computer-interaction, soft-computin deliberative multi-agent systems disciplines. Until recently, these were not able to be combined into a usable platform due largely to technological limitations (e.g., size, cost, and processing speed), insufficient research on extracting behavioral states from EEG signals, and lack of low-cost wireless sensing headsets. We aim to surpass these limitations and develop control architectures for making sense of brain state in applications by realizing an agent architecture for adaptive (human-aware) technology. In this paper we present an early, high-level design towards implementing a multi-purpose brain-monitoring agent system to improve user quality of life through the assistive applications of psycho-physiological monitoring, noise-filtering, and shared system control.
Breast tumor malignancy modelling using evolutionary neural logic networks.
Tsakonas, Athanasios; Dounias, Georgios; Panagi, Georgia; Panourgias, Evangelia
2006-01-01
The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.
A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications.
Amirkhani, Abdollah; Papageorgiou, Elpiniki I; Mohseni, Akram; Mosavi, Mohammad R
2017-04-01
A high percentage of medical errors, committed because of physician's lack of experience, huge volume of data to be analyzed, and inaccessibility to medical records of previous patients, can be reduced using computer-aided techniques. Therefore, designing more efficient medical decision-support systems (MDSSs) to assist physicians in decision-making is crucially important. Through combining the properties of fuzzy logic and neural networks, fuzzy cognitive maps (FCMs) are among the latest, most efficient, and strongest artificial intelligence techniques for modeling complex systems. This review study is conducted to identify different FCM structures used in MDSS designs. The best structure for each medical application can be introduced by studying the properties of FCM structures. This paper surveys the most important decision- making methods and applications of FCMs in the medical field in recent years. To investigate the efficiency and capability of different FCM models in designing MDSSs, medical applications are categorized into four key areas: decision-making, diagnosis, prediction, and classification. Also, various diagnosis and decision support problems addressed by FCMs in recent years are reviewed with the goal of introducing different types of FCMs and determining their contribution to the improvements made in the fields of medical diagnosis and treatment. In this survey, a general trend for future studies in this field is provided by analyzing various FCM structures used for medical purposes, and the results from each category. Due to the unique specifications of FCMs in integrating human knowledge and experience with computer-aided techniques, they are among practical instruments for MDSS design. In the not too distant future, they will have a significant role in medical sciences. Copyright © 2017 Elsevier B.V. All rights reserved.
2014-05-22
attempted to respond to the advances in technology and the growing power of geographical information system (GIS) tools. However, the doctrine...Geospatial intelligence (GEOINT), Geographical information systems (GIS) tools, Humanitarian Assistance/Disaster Relief (HA/DR), 2010 Haiti Earthquake...Humanitarian Assistance/Disaster Relief (HA/DR) Decisions Through Geospatial Intelligence (GEOINT) and Geographical Information Systems (GIS) Tools
Using the Computer in Special Vocational Programs. Inservice Activities.
ERIC Educational Resources Information Center
Lane, Kenneth; Ward, Raymond
This inservice manual is intended to assist vocational education teachers in using the techniques of computer-assisted instruction in special vocational education programs. Addressed in the individual units are the following topics: the basic principles of computer-assisted instruction (TRS-80 computers and typing on a computer keyboard); money…
ERIC Educational Resources Information Center
Gambari, Isiaka A.; Gbodi, Bimpe E.; Olakanmi, Eyitao U.; Abalaka, Eneojo N.
2016-01-01
The role of computer-assisted instruction in promoting intrinsic and extrinsic motivation among Nigerian secondary school chemistry students was investigated in this study. The study employed two modes of computer-assisted instruction (computer simulation instruction and computer tutorial instructional packages) and two levels of gender (male and…
NASA Astrophysics Data System (ADS)
Kim, Edward; Baloch, Zubair; Kim, Caroline
2015-03-01
The number of new cases of thyroid cancer are dramatically increasing as incidences of this cancer have more than doubled since the early 1970s. Tall cell variant (TCV-PTC) papillary thyroid carcinoma is one type of thyroid cancer that is more aggressive and usually associated with higher local recurrence and distant metastasis. This variant can be identified through visual characteristics of cells in histological images. Thus, we created a fully automatic algorithm that is able to segment cells using a multi-stage approach. Our method learns the statistical characteristics of nuclei and cells during the segmentation process and utilizes this information for a more accurate result. Furthermore, we are able to analyze the detected regions and extract characteristic cell data that can be used to assist in clinical diagnosis.
Marufuzzaman, M; Reaz, M B I; Ali, M A M; Rahman, L F
2015-01-01
The goal of smart homes is to create an intelligent environment adapting the inhabitants need and assisting the person who needs special care and safety in their daily life. This can be reached by collecting the ADL (activities of daily living) data and further analysis within existing computing elements. In this research, a very recent algorithm named sequence prediction via enhanced episode discovery (SPEED) is modified and in order to improve accuracy time component is included. The modified SPEED or M-SPEED is a sequence prediction algorithm, which modified the previous SPEED algorithm by using time duration of appliance's ON-OFF states to decide the next state. M-SPEED discovered periodic episodes of inhabitant behavior, trained it with learned episodes, and made decisions based on the obtained knowledge. The results showed that M-SPEED achieves 96.8% prediction accuracy, which is better than other time prediction algorithms like PUBS, ALZ with temporal rules and the previous SPEED. Since human behavior shows natural temporal patterns, duration times can be used to predict future events more accurately. This inhabitant activity prediction system will certainly improve the smart homes by ensuring safety and better care for elderly and handicapped people.
Computer vision and augmented reality in gastrointestinal endoscopy
Mahmud, Nadim; Cohen, Jonah; Tsourides, Kleovoulos; Berzin, Tyler M.
2015-01-01
Augmented reality (AR) is an environment-enhancing technology, widely applied in the computer sciences, which has only recently begun to permeate the medical field. Gastrointestinal endoscopy—which relies on the integration of high-definition video data with pathologic correlates—requires endoscopists to assimilate and process a tremendous amount of data in real time. We believe that AR is well positioned to provide computer-guided assistance with a wide variety of endoscopic applications, beginning with polyp detection. In this article, we review the principles of AR, describe its potential integration into an endoscopy set-up, and envisage a series of novel uses. With close collaboration between physicians and computer scientists, AR promises to contribute significant improvements to the field of endoscopy. PMID:26133175
NASA Astrophysics Data System (ADS)
Glotsos, Dimitris; Kostopoulos, Spiros; Lalissidou, Stella; Sidiropoulos, Konstantinos; Asvestas, Pantelis; Konstandinou, Christos; Xenogiannopoulos, George; Konstantina Nikolatou, Eirini; Perakis, Konstantinos; Bouras, Thanassis; Cavouras, Dionisis
2015-09-01
The purpose of this study was to design a decision support system for assisting the diagnosis of melanoma in dermatoscopy images. Clinical material comprised images of 44 dysplastic (clark's nevi) and 44 malignant melanoma lesions, obtained from the dermatology database Dermnet. Initially, images were processed for hair removal and background correction using the Dull Razor algorithm. Processed images were segmented to isolate moles from surrounding background, using a combination of level sets and an automated thresholding approach. Morphological (area, size, shape) and textural features (first and second order) were calculated from each one of the segmented moles. Extracted features were fed to a pattern recognition system assembled with the Probabilistic Neural Network Classifier, which was trained to distinguish between benign and malignant cases, using the exhaustive search and the leave one out method. The system was designed on the GPU card (GeForce 580GTX) using CUDA programming framework and C++ programming language. Results showed that the designed system discriminated benign from malignant moles with 88.6% accuracy employing morphological and textural features. The proposed system could be used for analysing moles depicted on smart phone images after appropriate training with smartphone images cases. This could assist towards early detection of melanoma cases, if suspicious moles were to be captured on smartphone by patients and be transferred to the physician together with an assessment of the mole's nature.
Wald Sequential Probability Ratio Test for Space Object Conjunction Assessment
NASA Technical Reports Server (NTRS)
Carpenter, James R.; Markley, F Landis
2014-01-01
This paper shows how satellite owner/operators may use sequential estimates of collision probability, along with a prior assessment of the base risk of collision, in a compound hypothesis ratio test to inform decisions concerning collision risk mitigation maneuvers. The compound hypothesis test reduces to a simple probability ratio test, which appears to be a novel result. The test satisfies tolerances related to targeted false alarm and missed detection rates. This result is independent of the method one uses to compute the probability density that one integrates to compute collision probability. A well-established test case from the literature shows that this test yields acceptable results within the constraints of a typical operational conjunction assessment decision timeline. Another example illustrates the use of the test in a practical conjunction assessment scenario based on operations of the International Space Station.
NASA Astrophysics Data System (ADS)
Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen
2005-02-01
An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.
Statistical modeling, detection, and segmentation of stains in digitized fabric images
NASA Astrophysics Data System (ADS)
Gururajan, Arunkumar; Sari-Sarraf, Hamed; Hequet, Eric F.
2007-02-01
This paper will describe a novel and automated system based on a computer vision approach, for objective evaluation of stain release on cotton fabrics. Digitized color images of the stained fabrics are obtained, and the pixel values in the color and intensity planes of these images are probabilistically modeled as a Gaussian Mixture Model (GMM). Stain detection is posed as a decision theoretic problem, where the null hypothesis corresponds to absence of a stain. The null hypothesis and the alternate hypothesis mathematically translate into a first order GMM and a second order GMM respectively. The parameters of the GMM are estimated using a modified Expectation-Maximization (EM) algorithm. Minimum Description Length (MDL) is then used as the test statistic to decide the verity of the null hypothesis. The stain is then segmented by a decision rule based on the probability map generated by the EM algorithm. The proposed approach was tested on a dataset of 48 fabric images soiled with stains of ketchup, corn oil, mustard, ragu sauce, revlon makeup and grape juice. The decision theoretic part of the algorithm produced a correct detection rate (true positive) of 93% and a false alarm rate of 5% on these set of images.
ERIC Educational Resources Information Center
Higgins, William R.
1987-01-01
Reviews a dissertation in which the problems of real-time pitch detection by computer were studied in an attempt to develop a learning tool for sightsinging students. Specialized hardware and software were developed to discriminate aural pitches and to display them in real-time using standard notation. (BSR)
Context-Aware Intelligent Assistant Approach to Improving Pilot's Situational Awareness
NASA Technical Reports Server (NTRS)
Spirkovska, Lilly; Lodha, Suresh K.
2004-01-01
Faulty decision making due to inaccurate or incomplete awareness of the situation tends to be the prevailing cause of fatal general aviation accidents. Of these accidents, loss of weather situational awareness accounts for the largest number of fatalities. We describe a method for improving weather situational awareness through the support of a contextaware,domain and task knowledgeable, personalized and adaptive assistant. The assistant automatically monitors weather reports for the pilot's route of flight and warns her of detected anomalies. When and how warnings are issued is determined by phase of flight, the pilot s definition of acceptable weather conditions, and the pilot's preferences for automatic notification. In addition to automatic warnings, the pilot is able to verbally query for weather and airport information. By noting the requests she makes during the approach phase of flight, our system learns to provide the information without explicit requests on subsequent flights with similar conditions. We show that our weather assistant decreases the effort required to maintain situational awareness by more than 5.5 times when compared to the conventional method of in-flight weather briefings.
Hirose, Tomohiro; Nitta, Norihisa; Shiraishi, Junji; Nagatani, Yukihiro; Takahashi, Masashi; Murata, Kiyoshi
2008-12-01
The aim of this study was to evaluate the usefulness of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector-row computed tomography (MDCT) in terms of improvement in radiologists' diagnostic accuracy in detecting lung nodules, using jackknife free-response receiver-operating characteristic (JAFROC) analysis. Twenty-one patients (6 without and 15 with lung nodules) were selected randomly from 120 consecutive thoracic computed tomographic examinations. The gold standard for the presence or absence of nodules in the observer study was determined by consensus of two radiologists. Six expert radiologists participated in a free-response receiver operating characteristic study for the detection of lung nodules on MDCT, in which cases were interpreted first without and then with the output of CAD software. Radiologists were asked to indicate the locations of lung nodule candidates on the monitor with their confidence ratings for the presence of lung nodules. The performance of the CAD software indicated that the sensitivity in detecting lung nodules was 71.4%, with 0.95 false-positive results per case. When radiologists used the CAD software, the average sensitivity improved from 39.5% to 81.0%, with an increase in the average number of false-positive results from 0.14 to 0.89 per case. The average figure-of-merit values for the six radiologists were 0.390 without and 0.845 with the output of the CAD software, and there was a statistically significant difference (P < .0001) using the JAFROC analysis. The CAD software for the detection of lung nodules on MDCT has the potential to assist radiologists by increasing their accuracy.
A two-view ultrasound CAD system for spina bifida detection using Zernike features
NASA Astrophysics Data System (ADS)
Konur, Umut; Gürgen, Fikret; Varol, Füsun
2011-03-01
In this work, we address a very specific CAD (Computer Aided Detection/Diagnosis) problem and try to detect one of the relatively common birth defects - spina bifida, in the prenatal period. To do this, fetal ultrasound images are used as the input imaging modality, which is the most convenient so far. Our approach is to decide using two particular types of views of the fetal neural tube. Transcerebellar head (i.e. brain) and transverse (axial) spine images are processed to extract features which are then used to classify healthy (normal), suspicious (probably defective) and non-decidable cases. Decisions raised by two independent classifiers may be individually treated, or if desired and data related to both modalities are available, those decisions can be combined to keep matters more secure. Even more security can be attained by using more than two modalities and base the final decision on all those potential classifiers. Our current system relies on feature extraction from images for cases (for particular patients). The first step is image preprocessing and segmentation to get rid of useless image pixels and represent the input in a more compact domain, which is hopefully more representative for good classification performance. Next, a particular type of feature extraction, which uses Zernike moments computed on either B/W or gray-scale image segments, is performed. The aim here is to obtain values for indicative markers that signal the presence of spina bifida. Markers differ depending on the image modality being used. Either shape or texture information captured by moments may propose useful features. Finally, SVM is used to train classifiers to be used as decision makers. Our experimental results show that a promising CAD system can be actualized for the specific purpose. On the other hand, the performance of such a system would highly depend on the qualities of image preprocessing, segmentation, feature extraction and comprehensiveness of image data.
Moses, M F
1994-12-01
Last May a federal judge struck down Washington State's law against assisted suicide on the grounds that it violated the U.S. Constitution. The judge ruled that just as a citizen has a right to refuse life-sustaining medical treatment, so does he or she have a right to request a physician's assistance in committing suicide. The court also concluded that because the decision to end one's life is as intimate and personal as a decision to have an abortion, assisted suicide must also be constitutionally protected. The court is mistaken. A "right" to assisted suicide is described nowhere in the text of the Constitution. Assisted suicide, furthermore, does not occupy a fundamental place in American history and traditions, and therefore cannot be deemed implicit in the constitutional guarantee of due process. Indeed, just the opposite is true: Our history and traditions actively discourage and prohibit assisted suicide. The asserted right to assisted suicide finds no support in cases involving either abortion or termination of medical treatment. Two terms ago, the Supreme Court relied heavily on stare decisis in upholding the abortion right, but there is no line of precedent for a right to assisted suicide. Not all "personal" decisions are constitutionally protected, so the personal nature of suicide does not dispose of the question of its constitutional status. Finally, in equating refusal of medical treatment with suicide, the federal court in Washington State ignores a long line of authority that recognizes a fundamental difference between the two.(ABSTRACT TRUNCATED AT 250 WORDS)
Development of a support tool for complex decision-making in the provision of rural maternity care.
Hearns, Glen; Klein, Michael C; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea
2010-02-01
Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology.
Development of a Support Tool for Complex Decision-Making in the Provision of Rural Maternity Care
Hearns, Glen; Klein, Michael C.; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea
2010-01-01
Context: Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. Objective: To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Design: Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Setting: Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Participants: Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). Results: We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Conclusions: Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology. PMID:21286270
Paquerault, Sophie; Hardy, Paul T; Wersto, Nancy; Chen, John; Smith, Robert C
2010-09-01
The aim of this study was to explore different computerized models (the "machine") as a means to achieve optimal use of computer-aided detection (CAD) systems and to investigate whether these models can play a primary role in clinical decision making and possibly replace a clinician's subjective decision for combining his or her own assessment with that provided by a CAD system. Data previously collected from a fully crossed, multiple-reader, multiple-case observer study with and without CAD by seven observers asked to identify simulated small masses on two separate sets of 100 mammographic images (low-contrast and high-contrast sets; ie, low-contrast and high-contrast simulated masses added to random locations on normal mammograms) were used. This allowed testing two relative sensitivities between the observers and CAD. Seven models that combined detection assessments from CAD standalone, unaided read, and CAD-aided read (second read and concurrent read) were developed using the leave-one-out technique for training and testing. These models were personalized for each observer. Detection performance accuracies were analyzed using the area under a portion of the free-response receiver-operating characteristic curve (AUFC), sensitivity, and number of false-positives per image. For the low-contrast set, the use of computerized models resulted in significantly higher AUFCs compared to the unaided read mode for all readers, whereas the increased AUFCs between CAD-aided (second and concurrent reads; ie, decisions made by the readers) and unaided read modes were statistically significant for a majority, but not all, of the readers (four and five of the seven readers, respectively). For the high-contrast set, there were no significant trends in the AUFCs whether or not a model was used to combine the original reading modes. Similar results were observed when using sensitivity as the figure of merit. However, the average number of false-positives per image resulting from the computerized models remained the same as that obtained from the unaided read modes. Individual computerized models (the machine) that combine image assessments from CAD standalone, unaided read, and CAD-aided read can increase detection performance compared to the reading done by the observer. However, relative sensitivity (ie, the difference in sensitivity between CAD standalone and unaided read) was a critical factor that determined incremental improvement in decision making, whether made by the observer or using computerized models. Published by Elsevier Inc.
Chai, Rifai; Naik, Ganesh R; Ling, Sai Ho; Nguyen, Hung T
2017-01-07
One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels. In addition, a microcontroller based head-mounted battery-operated wireless EEG sensor combined with a separate embedded system is used to enhance portability, convenience and cost effectiveness. This experiment has been conducted with five healthy participants and five patients with tetraplegia. Generally, the results show comparable classification accuracies between healthy subjects and tetraplegia patients. For the offline artificial neural network classification for the target group of patients with tetraplegia, the hybrid BCI system combines three mental tasks, three SSVEP frequencies and eyes closed, with average classification accuracy at 74% and average information transfer rate (ITR) of the system of 27 bits/min. For the real-time testing of the intentional signal on patients with tetraplegia, the average success rate of detection is 70% and the speed of detection varies from 2 to 4 s.
Assisting Movement Training and Execution With Visual and Haptic Feedback.
Ewerton, Marco; Rother, David; Weimar, Jakob; Kollegger, Gerrit; Wiemeyer, Josef; Peters, Jan; Maeda, Guilherme
2018-01-01
In the practice of motor skills in general, errors in the execution of movements may go unnoticed when a human instructor is not available. In this case, a computer system or robotic device able to detect movement errors and propose corrections would be of great help. This paper addresses the problem of how to detect such execution errors and how to provide feedback to the human to correct his/her motor skill using a general, principled methodology based on imitation learning. The core idea is to compare the observed skill with a probabilistic model learned from expert demonstrations. The intensity of the feedback is regulated by the likelihood of the model given the observed skill. Based on demonstrations, our system can, for example, detect errors in the writing of characters with multiple strokes. Moreover, by using a haptic device, the Haption Virtuose 6D, we demonstrate a method to generate haptic feedback based on a distribution over trajectories, which could be used as an auxiliary means of communication between an instructor and an apprentice. Additionally, given a performance measurement, the haptic device can help the human discover and perform better movements to solve a given task. In this case, the human first tries a few times to solve the task without assistance. Our framework, in turn, uses a reinforcement learning algorithm to compute haptic feedback, which guides the human toward better solutions.
Hefny, Ashraf F; Kunhivalappil, Fathima T; Matev, Nikolay; Avila, Norman A; Bashir, Masoud O; Abu-Zidan, Fikri M
2018-01-01
INTRODUCTION Diagnoses of pneumothorax, especially occult pneumothorax, have increased as the use of computed tomography (CT) for imaging trauma patients becomes near-routine. However, the need for chest tube insertion remains controversial. We aimed to study the management of pneumothorax detected on CT among patients with blunt trauma, including the decision for tube thoracostomy, in a community-based hospital. METHODS Chest CT scans of patients with blunt trauma treated at Al Rahba Hospital, Abu Dhabi, United Arab Emirates, from October 2010 to October 2014 were retrospectively studied. Variables studied included demography, mechanism of injury, endotracheal intubation, pneumothorax volume, chest tube insertion, Injury Severity Score, hospital length of stay and mortality. RESULTS CT was performed in 703 patients with blunt trauma. Overall, pneumothorax was detected on CT for 74 (10.5%) patients. Among the 65 patients for whom pneumothorax was detected before chest tube insertion, 25 (38.5%) needed chest tube insertion, while 40 (61.5%) did not. Backward stepwise likelihood regression showed that independent factors that significantly predicted chest tube insertion were endotracheal intubation (p = 0.01), non-United Arab Emirates nationality (p = 0.01) and pneumothorax volume (p = 0.03). The receiver operating characteristic curve showed that the best pneumothorax volume that predicted chest tube insertion was 30 mL. CONCLUSION Chest tube was inserted in less than half of the patients with blunt trauma for whom pneumothorax was detected on CT. Pneumothorax volume should be considered in decision-making regarding chest tube insertion. Conservative treatment may be sufficient for pneumothorax of volume < 30 mL. PMID:28741012
Hefny, Ashraf F; Kunhivalappil, Fathima T; Matev, Nikolay; Avila, Norman A; Bashir, Masoud O; Abu-Zidan, Fikri M
2018-03-01
Diagnoses of pneumothorax, especially occult pneumothorax, have increased as the use of computed tomography (CT) for imaging trauma patients becomes near-routine. However, the need for chest tube insertion remains controversial. We aimed to study the management of pneumothorax detected on CT among patients with blunt trauma, including the decision for tube thoracostomy, in a community-based hospital. Chest CT scans of patients with blunt trauma treated at Al Rahba Hospital, Abu Dhabi, United Arab Emirates, from October 2010 to October 2014 were retrospectively studied. Variables studied included demography, mechanism of injury, endotracheal intubation, pneumothorax volume, chest tube insertion, Injury Severity Score, hospital length of stay and mortality. CT was performed in 703 patients with blunt trauma. Overall, pneumothorax was detected on CT for 74 (10.5%) patients. Among the 65 patients for whom pneumothorax was detected before chest tube insertion, 25 (38.5%) needed chest tube insertion, while 40 (61.5%) did not. Backward stepwise likelihood regression showed that independent factors that significantly predicted chest tube insertion were endotracheal intubation (p = 0.01), non-United Arab Emirates nationality (p = 0.01) and pneumothorax volume (p = 0.03). The receiver operating characteristic curve showed that the best pneumothorax volume that predicted chest tube insertion was 30 mL. Chest tube was inserted in less than half of the patients with blunt trauma for whom pneumothorax was detected on CT. Pneumothorax volume should be considered in decision-making regarding chest tube insertion. Conservative treatment may be sufficient for pneumothorax of volume < 30 mL. Copyright: © Singapore Medical Association.
A source-attractor approach to network detection of radiation sources
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Qishi; Barry, M. L..; Grieme, M.
Radiation source detection using a network of detectors is an active field of research for homeland security and defense applications. We propose Source-attractor Radiation Detection (SRD) method to aggregate measurements from a network of detectors for radiation source detection. SRD method models a potential radiation source as a magnet -like attractor that pulls in pre-computed virtual points from the detector locations. A detection decision is made if a sufficient level of attraction, quantified by the increase in the clustering of the shifted virtual points, is observed. Compared with traditional methods, SRD has the following advantages: i) it does not requiremore » an accurate estimate of the source location from limited and noise-corrupted sensor readings, unlike the localizationbased methods, and ii) its virtual point shifting and clustering calculation involve simple arithmetic operations based on the number of detectors, avoiding the high computational complexity of grid-based likelihood estimation methods. We evaluate its detection performance using canonical datasets from Domestic Nuclear Detection Office s (DNDO) Intelligence Radiation Sensors Systems (IRSS) tests. SRD achieves both lower false alarm rate and false negative rate compared to three existing algorithms for network source detection.« less
Designing and Creating Computer-Assisted Instruction.
ERIC Educational Resources Information Center
McMeen, George R.
Designed to encourage the use of a defined methodology and careful planning in creating computer-assisted instructional programs, this paper describes the instructional design process, compares computer-assisted instruction (CAI) and programmed instruction (PI), and discusses pragmatic concerns in computer programming. Topics addressed include:…
Paul, Christine; Boyes, Allison; Hall, Alix; Bisquera, Alessandra; Miller, Annie; O'Brien, Lorna
2016-11-01
The financial impact of cancer diagnosis and treatment can be considerable to individuals and their households, leading to changes in treatment decision making. This study aimed to quantify effects on income and employment; describe how cost-related factors influence treatment decision making and need for financial assistance; and to identify patient sociodemographic factors associated with treatment decision making, use of financial assistance and financial effects. A cross-sectional self-report questionnaire was administered to oncology outpatients from two hospitals in Australia: one regional and one metropolitan. Of 255 participants, 67 % indicated a change in employment and 63 % of those reported reduced household income since their diagnosis. Travel (15 %), loss of income (14 %) and cost of treatments (11 %) were commonly cited factors influencing treatment decision making. Seventy-four percent of participants reported that they did not access financial assistance, with more than a third (37 %) of those being unaware that financial assistance was available. Being currently not employed and more recent diagnosis were associated with a reduced income since diagnosis. After adjusting for employment status and age, patients with private health insurance had higher odds of reporting that financial factors had influenced treatment decision making (OR = 2.5). Unemployment is a major driver of the financial impact of cancer. The costs of treatment may be particularly challenging for those with private health insurance who are more likely to be treated in the private health system where out-of-pocket costs are greater. Improved access to financial assistance is required to better avoid potential inequities.
Ko, Gi-Young; Kwon, Young Baek; Yoon, Hyun-Ki; Sung, Kyu-Bo
2018-01-01
Objective To investigate the technical and clinical outcomes of plug-assisted retrograde transvenous obliteration (PARTO) for the treatment of gastric varices (GV) and to evaluate the role of intra-procedural cone-beam computed tomography (CBCT) performed during PARTO to confirm its technical success. Materials and Methods From January 2016 to December 2016, 17 patients with GV who had undergone PARTO were retrospectively evaluated. When the proximal part of the afferent vein was identified on a fluoroscopy, non-contrast CBCT images were obtained. In patients with incomplete embolization of GV, an additional injection of gelatin sponges was performed. Follow-up data from contrast-enhanced CT and upper intestinal endoscopy, as well as clinical and laboratory data were collected. Results Plug-assisted retrograde transvenous obliteration procedures were technically successful in all 17 patients. Complete embolization of GV was detected on CBCT images in 15 patients; whereas, incomplete embolization was detected in two. Complete embolization of GV was then achieved after an additional injection of gelatin sponges in these two patients as demonstrated on the 2nd CBCT image. The mean follow-up period after PARTO was 193 days (range, 73–383 days). A follow-up CT obtained 2–4 months after PARTO demonstrated marked shrinkage or complete obliteration of GV and portosystemic shunts in all 17 patients. There were no cases of variceal bleeding during the follow-up. Conclusion Plug-assisted retrograde transvenous obliteration is technically and clinically effective for the treatment of GV. In addition, intra-procedural CBCT can be an adjunct tool to fluoroscopy, because it can provide an immediate and accurate evaluation of the technical success of PARTO. PMID:29520179
Toward retail product recognition on grocery shelves
NASA Astrophysics Data System (ADS)
Varol, Gül; Kuzu, Rıdvan S.
2015-03-01
This paper addresses the problem of retail product recognition on grocery shelf images. We present a technique for accomplishing this task with a low time complexity. We decompose the problem into detection and recognition. The former is achieved by a generic product detection module which is trained on a specific class of products (e.g. tobacco packages). Cascade object detection framework of Viola and Jones [1] is used for this purpose. We further make use of Support Vector Machines (SVMs) to recognize the brand inside each detected region. We extract both shape and color information; and apply feature-level fusion from two separate descriptors computed with the bag of words approach. Furthermore, we introduce a dataset (available on request) that we have collected for similar research purposes. Results are presented on this dataset of more than 5,000 images consisting of 10 tobacco brands. We show that satisfactory detection and classification can be achieved on devices with cheap computational power. Potential applications of the proposed approach include planogram compliance control, inventory management and assisting visually impaired people during shopping.
Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection
Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang
2018-01-01
In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10−5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced. PMID:29342963
2012-10-01
National Health and Nutrition Examination Survey (NHANES) data demonstrated that 42.3% of patients with DM have A1Cs over 7% (22). The military healthcare...system (MHS) - where there is no cost to the patient for care and testing supplies - has similar results with hemoglobin A1C’s over 7% in 42% of...Endocrinologists and Certified Diabetes Educators in both military and civilian health care settings (23), the vast majority of patients with DM are
Intelligent Computer-Assisted Language Learning.
ERIC Educational Resources Information Center
Harrington, Michael
1996-01-01
Introduces the field of intelligent computer assisted language learning (ICALL) and relates them to current practice in computer assisted language learning (CALL) and second language learning. Points out that ICALL applies expertise from artificial intelligence and the computer and cognitive sciences to the development of language learning…
Folan, Alyce; Barclay, Linda; Cooper, Cathy; Robinson, Merren
2015-01-01
Assistive technology for computer access can be used to facilitate people with a spinal cord injury to utilize mainstream computer applications, thereby enabling participation in a variety of meaningful occupations. The aim of this study was to gain an understanding of the experiences of clients with tetraplegia trialing assistive technologies for computer access during different stages in a public rehabilitation service. In order to explore the experiences of clients with tetraplegia trialing assistive technologies for computer use, qualitative methodology was selected. Data were collected from seven participants using semi-structured interviews, which were audio-taped, transcribed and analyzed thematically. Three main themes were identified. These were: getting back into life, assisting in adjusting to injury and learning new skills. The findings from this study demonstrated that people with tetraplegia can be assisted to return to previous life roles or engage in new roles, through developing skills in the use of assistive technology for computer access. Being able to use computers for meaningful activities contributed to the participants gaining an enhanced sense of self-efficacy, and thereby quality of life. Implications for Rehabilitation Findings from this pilot study indicate that people with tetraplegia can be assisted to return to previous life roles, and develop new roles that have meaning to them through the use of assistive technologies for computer use. Being able to use the internet to socialize, and complete daily tasks, contributed to the participants gaining a sense of control over their lives. Early introduction to assistive technology is important to ensure sufficient time for newly injured people to feel comfortable enough with the assistive technology to use the computers productively by the time of discharge. Further research into this important and expanding area is indicated.
Decision support environment for medical product safety surveillance.
Botsis, Taxiarchis; Jankosky, Christopher; Arya, Deepa; Kreimeyer, Kory; Foster, Matthew; Pandey, Abhishek; Wang, Wei; Zhang, Guangfan; Forshee, Richard; Goud, Ravi; Menschik, David; Walderhaug, Mark; Woo, Emily Jane; Scott, John
2016-12-01
We have developed a Decision Support Environment (DSE) for medical experts at the US Food and Drug Administration (FDA). The DSE contains two integrated systems: The Event-based Text-mining of Health Electronic Records (ETHER) and the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA). These systems assist medical experts in reviewing reports submitted to the Vaccine Adverse Event Reporting System (VAERS) and the FDA Adverse Event Reporting System (FAERS). In this manuscript, we describe the DSE architecture and key functionalities, and examine its potential contributions to the signal management process by focusing on four use cases: the identification of missing cases from a case series, the identification of duplicate case reports, retrieving cases for a case series analysis, and community detection for signal identification and characterization. Published by Elsevier Inc.
Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.
Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí
2014-11-28
The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.
Clinical Decision Support Systems (CDSS) for preventive management of COPD patients
2014-01-01
Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems. PMID:25471545
New 3D model for dynamics modeling
NASA Astrophysics Data System (ADS)
Perez, Alain
1994-05-01
The wrist articulation represents one of the most complex mechanical systems of the human body. It is composed of eight bones rolling and sliding along their surface and along the faces of the five metacarpals of the hand and the two bones of the arm. The wrist dynamics are however fundamental for the hand movement, but it is so complex that it still remains incompletely explored. This work is a part of a new concept of computer-assisted surgery, which consists in developing computer models to perfect surgery acts by predicting their consequences. The modeling of the wrist dynamics are based first on the static model of its bones in three dimensions. This 3D model must optimise the collision detection procedure which is the necessary step to estimate the physical contact constraints. As many other possible computer vision models do not fit with enough precision to this problem, a new 3D model has been developed thanks to the median axis of the digital distance map of the bones reconstructed volume. The collision detection procedure is then simplified for contacts are detected between spheres. The experiment of this original 3D dynamic model products realistic computer animation images of solids in contact. It is now necessary to detect ligaments on digital medical images and to model them in order to complete a wrist model.
Effects of automation of information-processing functions on teamwork.
Wright, Melanie C; Kaber, David B
2005-01-01
We investigated the effects of automation as applied to different stages of information processing on team performance in a complex decision-making task. Forty teams of 2 individuals performed a simulated Theater Defense Task. Four automation conditions were simulated with computer assistance applied to realistic combinations of information acquisition, information analysis, and decision selection functions across two levels of task difficulty. Multiple measures of team effectiveness and team coordination were used. Results indicated different forms of automation have different effects on teamwork. Compared with a baseline condition, an increase in automation of information acquisition led to an increase in the ratio of information transferred to information requested; an increase in automation of information analysis resulted in higher team coordination ratings; and automation of decision selection led to better team effectiveness under low levels of task difficulty but at the cost of higher workload. The results support the use of early and intermediate forms of automation related to acquisition and analysis of information in the design of team tasks. Decision-making automation may provide benefits in more limited contexts. Applications of this research include the design and evaluation of automation in team environments.
Computational Complexity and Human Decision-Making.
Bossaerts, Peter; Murawski, Carsten
2017-12-01
The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology. Copyright © 2017 Elsevier Ltd. All rights reserved.
Evidential reasoning research on intrusion detection
NASA Astrophysics Data System (ADS)
Wang, Xianpei; Xu, Hua; Zheng, Sheng; Cheng, Anyu
2003-09-01
In this paper, we mainly aim at D-S theory of evidence and the network intrusion detection these two fields. It discusses the method how to apply this probable reasoning as an AI technology to the Intrusion Detection System (IDS). This paper establishes the application model, describes the new mechanism of reasoning and decision-making and analyses how to implement the model based on the synscan activities detection on the network. The results suggest that if only rational probability values were assigned at the beginning, the engine can, according to the rules of evidence combination and hierarchical reasoning, compute the values of belief and finally inform the administrators of the qualities of the traced activities -- intrusions, normal activities or abnormal activities.
Metal surface corrosion grade estimation from single image
NASA Astrophysics Data System (ADS)
Chen, Yijun; Qi, Lin; Sun, Huyuan; Fan, Hao; Dong, Junyu
2018-04-01
Metal corrosion can cause many problems, how to quickly and effectively assess the grade of metal corrosion and timely remediation is a very important issue. Typically, this is done by trained surveyors at great cost. Assisting them in the inspection process by computer vision and artificial intelligence would decrease the inspection cost. In this paper, we propose a dataset of metal surface correction used for computer vision detection and present a comparison between standard computer vision techniques by using OpenCV and deep learning method for automatic metal surface corrosion grade estimation from single image on this dataset. The test has been performed by classifying images and calculating the accuracy for the two different approaches.
50 CFR 228.21 - Assistant Administrator's decision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 50 Wildlife and Fisheries 9 2011-10-01 2011-10-01 false Assistant Administrator's decision. 228.21 Section 228.21 Wildlife and Fisheries NATIONAL MARINE FISHERIES SERVICE, NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE MARINE MAMMALS NOTICE AND HEARING ON SECTION 103(d) REGULATIONS § 228.21...
14 CFR 303.46 - Decision by the Assistant Secretary.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Decision by the Assistant Secretary. 303.46 Section 303.46 Aeronautics and Space OFFICE OF THE SECRETARY, DEPARTMENT OF TRANSPORTATION (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS REVIEW OF AIR CARRIER AGREEMENTS Procedures Upon Application or Review...
Medical education as a science: the quality of evidence for computer-assisted instruction.
Letterie, Gerard S
2003-03-01
A marked increase in the number of computer programs for computer-assisted instruction in the medical sciences has occurred over the past 10 years. The quality of both the programs and the literature that describe these programs has varied considerably. The purposes of this study were to evaluate the published literature that described computer-assisted instruction in medical education and to assess the quality of evidence for its implementation, with particular emphasis on obstetrics and gynecology. Reports published between 1988 and 2000 on computer-assisted instruction in medical education were identified through a search of MEDLINE and Educational Resource Identification Center and a review of the bibliographies of the articles that were identified. Studies were selected if they included a description of computer-assisted instruction in medical education, regardless of the type of computer program. Data were extracted with a content analysis of 210 reports. The reports were categorized according to study design (comparative, prospective, descriptive, review, or editorial), type of computer-assisted instruction, medical specialty, and measures of effectiveness. Computer-assisted instruction programs included online technologies, CD-ROMs, video laser disks, multimedia work stations, virtual reality, and simulation testing. Studies were identified in all medical specialties, with a preponderance in internal medicine, general surgery, radiology, obstetrics and gynecology, pediatrics, and pathology. Ninety-six percent of the articles described a favorable impact of computer-assisted instruction in medical education, regardless of the quality of the evidence. Of the 210 reports that were identified, 60% were noncomparative, descriptive reports of new techniques in computer-assisted instruction, and 15% and 14% were reviews and editorials, respectively, of existing technology. Eleven percent of studies were comparative and included some form of assessment of the effectiveness of the computer program. These assessments included pre- and posttesting and questionnaires to score program quality, perceptions of the medical students and/or residents regarding the program, and impact on learning. In one half of these comparative studies, computer-assisted instruction was compared with traditional modes of teaching, such as text and lectures. Six studies compared performance before and after the computer-assisted instruction. Improvements were shown in 5 of the studies. In the remainder of the studies, computer-assisted instruction appeared to result in similar test performance. Despite study design or outcome, most articles described enthusiastic endorsement of the programs by the participants, including medical students, residents, and practicing physicians. Only 1 study included cost analysis. Thirteen of the articles were in obstetrics and gynecology. Computer-assisted instruction has assumed to have an increasing role in medical education. In spite of enthusiastic endorsement and continued improvements in software, few studies of good design clearly demonstrate improvement in medical education over traditional modalities. There are no comparative studies in obstetrics and gynecology that demonstrate a clear-cut advantage. Future studies of computer-assisted instruction that include comparisons and cost assessments to gauge their effectiveness over traditional methods may better define their precise role.
Multi-stage methodology to detect health insurance claim fraud.
Johnson, Marina Evrim; Nagarur, Nagen
2016-09-01
Healthcare costs in the US, as well as in other countries, increase rapidly due to demographic, economic, social, and legal changes. This increase in healthcare costs impacts both government and private health insurance systems. Fraudulent behaviors of healthcare providers and patients have become a serious burden to insurance systems by bringing unnecessary costs. Insurance companies thus develop methods to identify fraud. This paper proposes a new multistage methodology for insurance companies to detect fraud committed by providers and patients. The first three stages aim at detecting abnormalities among providers, services, and claim amounts. Stage four then integrates the information obtained in the previous three stages into an overall risk measure. Subsequently, a decision tree based method in stage five computes risk threshold values. The final decision stating whether the claim is fraudulent is made by comparing the risk value obtained in stage four with the risk threshold value from stage five. The research methodology performs well on real-world insurance data.
Quétard, Boris; Quinton, Jean-Charles; Colomb, Michèle; Pezzulo, Giovanni; Barca, Laura; Izaute, Marie; Appadoo, Owen Kevin; Mermillod, Martial
2015-09-01
Detecting a pedestrian while driving in the fog is one situation where the prior expectation about the target presence is integrated with the noisy visual input. We focus on how these sources of information influence the oculomotor behavior and are integrated within an underlying decision-making process. The participants had to judge whether high-/low-density fog scenes displayed on a computer screen contained a pedestrian or a deer by executing a mouse movement toward the response button (mouse-tracking). A variable road sign was added on the scene to manipulate expectations about target identity. We then analyzed the timing and amplitude of the deviation of mouse trajectories toward the incorrect response and, using an eye tracker, the detection time (before fixating the target) and the identification time (fixations on the target). Results revealed that expectation of the correct target results in earlier decisions with less deviation toward the alternative response, this effect being partially explained by the facilitation of target identification.
Covariance of lucky images: performance analysis
NASA Astrophysics Data System (ADS)
Cagigal, Manuel P.; Valle, Pedro J.; Cagigas, Miguel A.; Villó-Pérez, Isidro; Colodro-Conde, Carlos; Ginski, C.; Mugrauer, M.; Seeliger, M.
2017-01-01
The covariance of ground-based lucky images is a robust and easy-to-use algorithm that allows us to detect faint companions surrounding a host star. In this paper, we analyse the relevance of the number of processed frames, the frames' quality, the atmosphere conditions and the detection noise on the companion detectability. This analysis has been carried out using both experimental and computer-simulated imaging data. Although the technique allows us the detection of faint companions, the camera detection noise and the use of a limited number of frames reduce the minimum detectable companion intensity to around 1000 times fainter than that of the host star when placed at an angular distance corresponding to the few first Airy rings. The reachable contrast could be even larger when detecting companions with the assistance of an adaptive optics system.
Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.
Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab
2017-09-01
Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.
Herrick, D B; Nakhasi, A; Nelson, B; Rice, S; Abbott, P A; Saber Tehrani, A S; Rothman, R E; Lehmann, H P; Newman-Toker, D E
2013-01-01
Self-administered computer-assisted interviewing (SACAI) gathers accurate information from patients and could facilitate Emergency Department (ED) diagnosis. As part of an ongoing research effort whose long-range goal is to develop automated medical interviewing for diagnostic decision support, we explored usability attributes of SACAI in the ED. Cross-sectional study at two urban, academic EDs. Convenience sample recruited daily over six weeks. Adult, non-level I trauma patients were eligible. We collected data on ease of use (self-reported difficulty, researcher documented need for help), efficiency (mean time-per-click on a standardized interview segment), and error (self-report age mismatched with age derived from electronic health records) when using SACAI on three different instruments: Elo TouchSystems ESY15A2 (finger touch), Toshiba M200 (with digitizer pen), and Motion C5 (with digitizer pen). We calculated descriptive statistics and used regression analysis to evaluate the impact of patient and computer factors on time-per-click. 841 participants completed all SACAI questions. Few (<1%) thought using the touch computer to ascertain medical information was difficult. Most (86%) required no assistance. Participants needing help were older (54 ± 19 vs. 40 ± 15 years, p<0.001) and more often lacked internet at home (13.4% vs. 7.3%, p = 0.004). On multivariate analysis, female sex (p<0.001), White (p<0.001) and other (p = 0.05) race (vs. Black race), younger age (p<0.001), internet access at home (p<0.001), high school graduation (p = 0.04), and touch screen entry (vs. digitizer pen) (p = 0.01) were independent predictors of decreased time-per-click. Participant misclick errors were infrequent, but, in our sample, occurred only during interviews using a digitizer pen rather than a finger touch-screen interface (1.9% vs. 0%, p = 0.09). Our results support the facility of interactions between ED patients and SACAI. Demographic factors associated with need for assistance or slower interviews could serve as important triggers to offering human support for SACAI interviews during implementation. Understanding human-computer interactions in real-world clinical settings is essential to implementing automated interviewing as means to a larger long-term goal of enhancing clinical care, diagnostic accuracy, and patient safety.
Herrick, D. B.; Nakhasi, A.; Nelson, B.; Rice, S.; Abbott, P. A.; Saber Tehrani, A. S.; Rothman, R. E.; Lehmann, H. P.; Newman-Toker, D. E.
2013-01-01
Objective Self-administered computer-assisted interviewing (SACAI) gathers accurate information from patients and could facilitate Emergency Department (ED) diagnosis. As part of an ongoing research effort whose long-range goal is to develop automated medical interviewing for diagnostic decision support, we explored usability attributes of SACAI in the ED. Methods Cross-sectional study at two urban, academic EDs. Convenience sample recruited daily over six weeks. Adult, non-level I trauma patients were eligible. We collected data on ease of use (self-reported difficulty, researcher documented need for help), efficiency (mean time-per-click on a standardized interview segment), and error (self-report age mismatched with age derived from electronic health records) when using SACAI on three different instruments: Elo TouchSystems ESY15A2 (finger touch), Toshiba M200 (with digitizer pen), and Motion C5 (with digitizer pen). We calculated descriptive statistics and used regression analysis to evaluate the impact of patient and computer factors on time-per-click. Results 841 participants completed all SACAI questions. Few (<1%) thought using the touch computer to ascertain medical information was difficult. Most (86%) required no assistance. Participants needing help were older (54 ± 19 vs. 40 ± 15 years, p<0.001) and more often lacked internet at home (13.4% vs. 7.3%, p = 0.004). On multivariate analysis, female sex (p<0.001), White (p<0.001) and other (p = 0.05) race (vs. Black race), younger age (p<0.001), internet access at home (p<0.001), high school graduation (p = 0.04), and touch screen entry (vs. digitizer pen) (p = 0.01) were independent predictors of decreased time-per-click. Participant misclick errors were infrequent, but, in our sample, occurred only during interviews using a digitizer pen rather than a finger touch-screen interface (1.9% vs. 0%, p = 0.09). Discussion Our results support the facility of interactions between ED patients and SACAI. Demographic factors associated with need for assistance or slower interviews could serve as important triggers to offering human support for SACAI interviews during implementation. Conclusion Understanding human-computer interactions in real-world clinical settings is essential to implementing automated interviewing as means to a larger long-term goal of enhancing clinical care, diagnostic accuracy, and patient safety. PMID:23874364
Computer Assisted Learning in Numeracy.
ERIC Educational Resources Information Center
Hollin, Freda
Computer-assisted learning in numeracy for adults is far less developed than computer-assisted learning in literacy. Although a great many software programs exist, few are suitable for adults and many offer only drill and practice exercises instead of teaching genuine computer skills. One approach instructors can take is to have their students use…
Improving drug safety: From adverse drug reaction knowledge discovery to clinical implementation.
Tan, Yuxiang; Hu, Yong; Liu, Xiaoxiao; Yin, Zhinan; Chen, Xue-Wen; Liu, Mei
2016-11-01
Adverse drug reactions (ADRs) are a major public health concern, causing over 100,000 fatalities in the United States every year with an annual cost of $136 billion. Early detection and accurate prediction of ADRs is thus vital for drug development and patient safety. Multiple scientific disciplines, namely pharmacology, pharmacovigilance, and pharmacoinformatics, have been addressing the ADR problem from different perspectives. With the same goal of improving drug safety, this article summarizes and links the research efforts in the multiple disciplines into a single framework from comprehensive understanding of the interactions between drugs and biological system and the identification of genetic and phenotypic predispositions of patients susceptible to higher ADR risks and finally to the current state of implementation of medication-related decision support systems. We start by describing available computational resources for building drug-target interaction networks with biological annotations, which provides a fundamental knowledge for ADR prediction. Databases are classified by functions to help users in selection. Post-marketing surveillance is then introduced where data-driven approach can not only enhance the prediction accuracy of ADRs but also enables the discovery of genetic and phenotypic risk factors of ADRs. Understanding genetic risk factors for ADR requires well organized patient genetics information and analysis by pharmacogenomic approaches. Finally, current state of clinical decision support systems is presented and described how clinicians can be assisted with the integrated knowledgebase to minimize the risk of ADR. This review ends with a discussion of existing challenges in each of disciplines with potential solutions and future directions. Copyright © 2016 Elsevier Inc. All rights reserved.
Decision Criterion Dynamics in Animals Performing an Auditory Detection Task
Mill, Robert W.; Alves-Pinto, Ana; Sumner, Christian J.
2014-01-01
Classical signal detection theory attributes bias in perceptual decisions to a threshold criterion, against which sensory excitation is compared. The optimal criterion setting depends on the signal level, which may vary over time, and about which the subject is naïve. Consequently, the subject must optimise its threshold by responding appropriately to feedback. Here a series of experiments was conducted, and a computational model applied, to determine how the decision bias of the ferret in an auditory signal detection task tracks changes in the stimulus level. The time scales of criterion dynamics were investigated by means of a yes-no signal-in-noise detection task, in which trials were grouped into blocks that alternately contained easy- and hard-to-detect signals. The responses of the ferrets implied both long- and short-term criterion dynamics. The animals exhibited a bias in favour of responding “yes” during blocks of harder trials, and vice versa. Moreover, the outcome of each single trial had a strong influence on the decision at the next trial. We demonstrate that the single-trial and block-level changes in bias are a manifestation of the same criterion update policy by fitting a model, in which the criterion is shifted by fixed amounts according to the outcome of the previous trial and decays strongly towards a resting value. The apparent block-level stabilisation of bias arises as the probabilities of outcomes and shifts on single trials mutually interact to establish equilibrium. To gain an intuition into how stable criterion distributions arise from specific parameter sets we develop a Markov model which accounts for the dynamic effects of criterion shifts. Our approach provides a framework for investigating the dynamics of decisions at different timescales in other species (e.g., humans) and in other psychological domains (e.g., vision, memory). PMID:25485733
Eichfeld, Uwe; Dietrich, Arne; Ott, Rudolph; Kloeppel, Rainer
2005-01-01
Peripheral pulmonary nodules are preferably removed by minimally invasive techniques, such as video-assisted thoracoscopic (VATS) surgery. These nodules should be marked preoperatively for better intraoperative detection and removal. Twenty-two cases with a single pulmonary nodule requiring surgical removal for histologic examination were included in a prospective study. Guided by computed tomography, nodules were marked preoperatively using a laser marker system and fixed with a spiral wire. The marked nodules were removed by VATS surgery immediately after the marking. The marking wire was placed in all 22 patients without any complications. The marked nodule was completely removed by VATS surgery in 19 patients. Conversion to thoracotomy was necessary in 3 patients, twice because of thoracoscopy-related problems and once because of a marking failure. The average times for the marking procedure and operation were 24 minutes and 32 minutes, respectively. This new method of computed tomography-guided nodule marking with a spiral wire and subsequent VATS surgery is very efficient in terms of localization and stable fixation of subpleural pulmonary nodules.
45 CFR 233.34 - Computing the assistance payment in the initial one or two months (AFDC).
Code of Federal Regulations, 2010 CFR
2010-10-01
... 45 Public Welfare 2 2010-10-01 2010-10-01 false Computing the assistance payment in the initial... § 233.34 Computing the assistance payment in the initial one or two months (AFDC). A State shall compute...) If the initial month is computed prospectively as in paragraph (a) of this section, the second month...
Machine Learning in Medical Imaging.
Giger, Maryellen L
2018-03-01
Advances in both imaging and computers have synergistically led to a rapid rise in the potential use of artificial intelligence in various radiological imaging tasks, such as risk assessment, detection, diagnosis, prognosis, and therapy response, as well as in multi-omics disease discovery. A brief overview of the field is given here, allowing the reader to recognize the terminology, the various subfields, and components of machine learning, as well as the clinical potential. Radiomics, an expansion of computer-aided diagnosis, has been defined as the conversion of images to minable data. The ultimate benefit of quantitative radiomics is to (1) yield predictive image-based phenotypes of disease for precision medicine or (2) yield quantitative image-based phenotypes for data mining with other -omics for discovery (ie, imaging genomics). For deep learning in radiology to succeed, note that well-annotated large data sets are needed since deep networks are complex, computer software and hardware are evolving constantly, and subtle differences in disease states are more difficult to perceive than differences in everyday objects. In the future, machine learning in radiology is expected to have a substantial clinical impact with imaging examinations being routinely obtained in clinical practice, providing an opportunity to improve decision support in medical image interpretation. The term of note is decision support, indicating that computers will augment human decision making, making it more effective and efficient. The clinical impact of having computers in the routine clinical practice may allow radiologists to further integrate their knowledge with their clinical colleagues in other medical specialties and allow for precision medicine. Copyright © 2018. Published by Elsevier Inc.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-07-10
...: Pretrial Technical Assistance for Evidence-Based Decision Making in Local Criminal Justice Systems AGENCY... NIC initiative, Evidence-Based Decision Making (EBDM) in Local Criminal Justice Systems. Work under... individual system planning activities. These change strategies are critical to meeting their system's harm...
Cai, Wenli; Lee, June-Goo; Fikry, Karim; Yoshida, Hiroyuki; Novelline, Robert; de Moya, Marc
2013-01-01
It is commonly believed that the size of a pneumothorax is an important determinant of treatment decision, in particular regarding whether chest tube drainage (CTD) is required. However, the volumetric quantification of pneumothoraces has not routinely been performed in clinics. In this paper, we introduced an automated computer-aided volumetry (CAV) scheme for quantification of volume of pneumothoraces in chest multi-detect CT (MDCT) images. Moreover, we investigated the impact of accurate volume of pneumothoraces in the improvement of the performance in decision-making regarding CTD in the management of traumatic pneumothoraces. For this purpose, an occurrence frequency map was calculated for quantitative analysis of the importance of each clinical parameter in the decision-making regarding CTD by a computer simulation of decision-making using a genetic algorithm (GA) and a support vector machine (SVM). A total of 14 clinical parameters, including volume of pneumothorax calculated by our CAV scheme, was collected as parameters available for decision-making. The results showed that volume was the dominant parameter in decision-making regarding CTD, with an occurrence frequency value of 1.00. The results also indicated that the inclusion of volume provided the best performance that was statistically significant compared to the other tests in which volume was excluded from the clinical parameters. This study provides the scientific evidence for the application of CAV scheme in MDCT volumetric quantification of pneumothoraces in the management of clinically stable chest trauma patients with traumatic pneumothorax. PMID:22560899
Detecting Surgical Tools by Modelling Local Appearance and Global Shape.
Bouget, David; Benenson, Rodrigo; Omran, Mohamed; Riffaud, Laurent; Schiele, Bernt; Jannin, Pierre
2015-12-01
Detecting tools in surgical videos is an important ingredient for context-aware computer-assisted surgical systems. To this end, we present a new surgical tool detection dataset and a method for joint tool detection and pose estimation in 2d images. Our two-stage pipeline is data-driven and relaxes strong assumptions made by previous works regarding the geometry, number, and position of tools in the image. The first stage classifies each pixel based on local appearance only, while the second stage evaluates a tool-specific shape template to enforce global shape. Both local appearance and global shape are learned from training data. Our method is validated on a new surgical tool dataset of 2 476 images from neurosurgical microscopes, which is made freely available. It improves over existing datasets in size, diversity and detail of annotation. We show that our method significantly improves over competitive baselines from the computer vision field. We achieve 15% detection miss-rate at 10(-1) false positives per image (for the suction tube) over our surgical tool dataset. Results indicate that performing semantic labelling as an intermediate task is key for high quality detection.
Detection of seizures from small samples using nonlinear dynamic system theory.
Yaylali, I; Koçak, H; Jayakar, P
1996-07-01
The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D2) of EEG time series data. In this paper, D2 of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D2 computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D2 computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies.
Preaching What We Practice: Teaching Ethical Decision-Making to Computer Security Professionals
NASA Astrophysics Data System (ADS)
Fleischmann, Kenneth R.
The biggest challenge facing computer security researchers and professionals is not learning how to make ethical decisions; rather it is learning how to recognize ethical decisions. All too often, technology development suffers from what Langdon Winner terms technological somnambulism - we sleepwalk through our technology design, following past precedents without a second thought, and fail to consider the perspectives of other stakeholders [1]. Computer security research and practice involves a number of opportunities for ethical decisions. For example, decisions about whether or not to automatically provide security updates involve tradeoffs related to caring versus user autonomy. Decisions about online voting include tradeoffs between convenience and security. Finally, decisions about routinely screening e-mails for spam involve tradeoffs of efficiency and privacy. It is critical that these and other decisions facing computer security researchers and professionals are confronted head on as value-laden design decisions, and that computer security researchers and professionals consider the perspectives of various stakeholders in making these decisions.
Methodological approaches of health technology assessment.
Goodman, C S; Ahn, R
1999-12-01
In this era of evolving health care systems throughout the world, technology remains the substance of health care. Medical informatics comprises a growing contribution to the technologies used in the delivery and management of health care. Diverse, evolving technologies include artificial neural networks, computer-assisted surgery, computer-based patient records, hospital information systems, and more. Decision-makers increasingly demand well-founded information to determine whether or how to develop these technologies, allow them on the market, acquire them, use them, pay for their use, and more. The development and wider use of health technology assessment (HTA) reflects this demand. While HTA offers systematic, well-founded approaches for determining the value of medical informatics technologies, HTA must continue to adapt and refine its methods in response to these evolving technologies. This paper provides a basic overview of HTA principles and methods.